Preprints.org logo
Preprint
Article

This version is not peer-reviewed.

Exome Sequencing of Premature Adult Deaths in the Population-Based Polish WOBASZ Study: High Yield of Reportable Findings

  # These authors contributed equally to this work.

Submitted:

14 September 2026

Posted:

15 September 2026

You are already at the latest version

Abstract
Premature adult death (PAD) may conceal clinically relevant monogenic disease. We performed exome sequencing in 127 deceased participants of the population-based Polish WOBASZ study (91 males, 36 females; mean age at death 47 years, range 26–55). Reportable variants were identified in 52 individuals (40.9%); after excluding low-penetrance risk factors and speculative findings, 39 (30.7%) remained. Genetic findings were considered highly likely to have contributed to cause of death in 9 (7.1%) and moderately likely in 16 (12.6%). Thirteen participants (10.2%) carried reportable variants in genes on the ACMG secondary findings list. Cancer-predisposition variants were enriched relative to 1,000 reference adults [3.9% vs 1.5%; Odds ratio (OR) 2.7, p=0.065], and genotype–cause-of-death concordance was greater for cancer than non-cancer ACMG findings (3/5 vs 0/8; OR 23.8, p=0.035). Broadly defined genetic cancer predisposition was present in 8 (28.6%) cancer deaths, involving BRCA1, BRCA2, MSH6, EPCAM, RAD51D, CHEK2 and JAK2. Additional findings included dominant neurodevelopmental variants, variants in genes associated with cardiomyopathy and vascular disease, two 22q11.2 deletions, and candidate novel associations implicating DROSHA, KCNQ1 and LZTS1 in germline cancer predisposition and EOLA2 and ARID4A in metabolic or neurodevelopmental disease. These results support broad exome/genome-based molecular autopsy in PAD.
Keywords: 
exome sequencing
;  
premature adult death
;  
molecular autopsy
;  
monogenic disorders
;  
genetic predisposition
;  
cause of death
;  
cancer predysposition
Subject: 
Medicine and Pharmacology  -   Other

Introduction

Premature adult deaths (PAD) are important because they result in the loss of potential years of life. An important category of PAD comprises cases caused by monogenic diseases whose diagnosis, even postmortem, is relevant to establishing cause of death (COD) and providing counselling for relatives.
Monogenic causes of PAD have been extensively investigated in selected cohorts with relatively high probability of cardiac disease [1,2,3,4] or epilepsy [5]. However, representative studies assessing the overall contribution of Mendelian disorders to all-cause PAD remain scarce.
It should be noted that even deaths attributed to external or unknown causes may have a genetic contribution. Inherited arrhythmias or epilepsy may precipitate accidents and psychiatric disorders may contribute to suicidal behavior [6,7,8,9]. It is also conceivable that unrecognized contributions to PAD may arise from neurodevelopmental disorders currently known mainly from their pediatric presentations.
The purpose of our study was to estimate, in a population-based cohort, the proportion of premature adult deaths potentially attributable to or influenced by a monogenic disease.

Materials and Methods

Ethical Approval

The current study was approved by the Local Bioethics Committee at the Institute of Cardiology (decision IK-NP-0021-60/1449/14). The original WOBASZ study was approved by the same Committee (decision IK-NP-0021-79/1396/13).

Study Population

The current study relied on DNA samples isolated from peripheral EDTA blood from participants in The Polish National Multicenter Health Survey (WOBASZ study). WOBASZ was a nationwide, cross-sectional study on classical and genetic risk factors for cardiovascular disease conducted in 2003–2005 across Poland. It was based on random sampling of a representative population sample with an age range of 20–74 years; the response rate was 70% [10].
The 127 DNA samples used in the current study came from WOBASZ respondents who were identified as having died between 2004 and 2012. The group comprised 91 males, 36 females, a mean age at death of 47 years (range 26–55 years). Causes of death were: malignant neoplasms (N=28), cardiovascular diseases (CVD, N=20), accidents (N=16), liver cirrhosis (N=7), other medical causes (N=8), unknown/undetermined (N=48).
As a reference for the analysis of variants in genes on the ACMG secondary findings list [11], we used aggregated data from our laboratory including 1,000 healthy adults most recently analyzed as parents in trio exome sequencing (ES).

DNA Sequencing and Data Analysis

ES libraries were prepared using the Illumina Nextera Rapid Capture Exome kit (45 Mb) and sequenced on a HiSeq 1500 platform (2 × 100 bp, Illumina). Technical summary of the sequencing results is presented in Supplementary Table 1. ES data were analyzed as described previously [12] except that for copy-number variant (CNV) calling DECoN [13] was used in addition to CNVKit [14] and HGMD was not used for annotation. The GRCh38 genome assembly was used in all analyses. The analysis was performed manually by analysts experienced in diagnostic ES. Final pathogenicity classification of single-nucleotide variants (SNVs) [Pathogenic (P), Likely Pathogenic (LP), Variant of Uncertain Significance (VUS), etc.] was performed using GeneBe.net [15] according to ACMG criteria [16] using a point-based framework [17]. Fisher’s exact test p-values and odds ratios (ORs) were calculated with www.socscistatistics.com/tests/fisher/calculator.

Results

General Findings

In 52 (40.9%) respondents we found at least one reportable variant (SNVs in 49, CNV in 3, Table 1). Sixteen persons had SNVs indicating cancer predisposition, 5 had predisposition to neurodevelopmental disorders, 3 - to CVD (cardiomyopathy), and 12 - to other Mendelian disorders with relatively high penetrance. In 11 respondents relatively low-penetrance SNVs (risk factors) were found whereas 2 had variants which may point to novel diseases (Table 1). When “novel” diseases and low-penetrance risk factors were excluded 39 (30.7%) persons remained.
In 9 persons (7.1%) the contribution of genetic findings to COD was regarded as highly likely. In 6 cases, cancer predisposition correlated with COD; in 1, predisposition to hematological malignancy (JAK2 variant) was identified in a person who died from an unknown cause; in the remaining 2, variants were consistent with stroke susceptibility (TEK, with possible contribution from PKD1) and HTT pathogenic expansion consistent with Huntington disease (Table 1).
In 16 persons (12.6%) the plausibility of a link with COD was regarded as moderate, mainly based on the possibility that the genetic findings contributed to PAD even when COD was unknown (N=11). The diseases predicted in this group included cancer (N=2), cardiomyopathy (N=3), vascular disorders (N=2), disorders from the spectrum of 22q11.2 (DiGeorge region) deletion (N=2) and single cases of nephrotic syndrome, Malan syndrome, Crouzon syndrome, spinocerebellar ataxia and pustular psoriasis (Table 1).
In 27 persons (21.3%) the plausibility of contribution to COD was low or none. This group included findings clearly discrepant with COD, especially when they constituted low-penetrance risk factors. In 4 cases the link was labelled as speculative because it involved a novel or poorly established gene-disease association.

Variants in Genes on the ACMG Secondary Findings List

Thirteen (10.2%) respondents had variants reportable according to the ACMG recommendations for secondary findings (Table 1, “ACMG” in genetic finding category) [11]. These included 6 respondents with predicted predisposition to cardiovascular disease (CVD) and 5 with predisposition to cancer. Table 2 shows distribution of persons with ACMG variants among the studied WOBASZ population and a reference population. The prevalence of persons with P/LP variants in the ACMG genes was not significantly higher in WOBASZ than in the reference population; however, we noted a trend when cancer genes were analyzed separately (3.9% vs 1.5%, for WOBASZ and the reference population, respectively, p = 0.065, OR = 2.7, Fisher’s exact test).
In 3 of the 5 respondents (60%) with variants in ACMG cancer-predisposition genes, COD was directly linked to the detected predisposition: breast and ovarian cancer in women with variants in BRCA1 and BRCA2, respectively, and cervical cancer in a female with variants in MSH6 and EPCAM. In contrast, none of the 8 respondents with predisposition associated with non-cancer ACMG genes had COD concordant with the identified susceptibility - 3 respondents with variants in TNNC1, KCNQ1 and GPR179 died from cancer; in another 3 with variants in DSG2, MYBPC3, MYH7 COD was unknown, whereas single respondents with FBN1 or HFE variants died in an accident or epidural hemorrhage, respectively.
The difference in the apparent penetrance of the detected predisposition for cancer vs non-cancer ACMG genes was statistically significant: 3/5 vs. 0/8, p=0.035 (Fisher’s exact test), OR = 23.8.

Cancer Predisposition

Twenty-eight (22.0%) respondents died from cancer. In 6 respondents (4.7%), well-known genetic variants were considered highly plausible contributors to COD. These included variants in BRCA1, BRCA2, RAD51D and CHEK2 in respondents who died from breast, ovarian, oral and cancer of unknown origin, respectively. One female who died from cervical cancer had two pathogenic variants in MSH6 and EPCAM. A novel LP variant in JAK2 was found in a female who died at age 53 years from a hematological malignancy. Given no evidence for mosaicism (variant present in 43% (17/40) reads) and a relatively long time between blood sampling and death (7 years), it is likely, although not proven, that the variant was germline.
Four of the 7 (57.1%) variants linked to cancer death (RAD51D, CHEK2, EPCAM and JAK2) are not included in the ACMG list [11].
In 3 individuals who died from cancer, we found variants whose contribution is speculative. These included KCNQ1 Arg259His variant in a participant who died from esophageal cancer, a heterozygous truncating variant in DROSHA (p.Arg295Ter) and a ~2.3 Mb dup (8)(p22-p21.3) possibly disrupting LZTS1 in 2 persons who died from lung/bronchial cancer.
Among the 28 WOBASZ respondents who died from cancer, in addition to 3 ACMG cancer-predisposition variants (in the BRCA1, BRCA2, MSH6 genes) there were 6 additional variants which might have contributed to death. These included 4 variants in genes already associated with cancer - JAK2, RAD51D, CHEK2, EPCAM (present together with an ACMG variant in MSH6) and 2 whose association with cancer is novel/emerging (DROSHA, LZTS1). The total number of respondents who died from cancer with any type of genetic predisposition was 8.
In 8 respondents we detected cancer predisposition not correlated with COD. Three of those included monoallelic LOF variants in LZTR1 (two frameshift variants and one whole-gene loss as part of a larger 22q11.2 deletion). While LOF of LZTR1 is a risk factor for schwannomatosis (OMIM#600574) the carriers died in an accident, unknown cause or nonallergic asthma. The remaining 5 respondents had monoallelic P/LP variants in BRCA2, BARD1, PALB2, TSC2 or FANCM (Table 1).

Neurodevelopmental Disorders

In 5 (4%) respondents we found P/LP SNVs in genes associated with dominant neurodevelopmental disorders (Table 1, ND): NFIX, GRIA2, BRPF1, SHANK2 or KCNQ2 (16% mosaic, a CREB3L3 variant also present). In the person with KCNQ2/CREB3L3 variants, the death was caused by liver cirrhosis; in the individual with GRIA2 variant – by acute respiratory failure; in the remaining 3 respondents, the COD was unknown. In the male with the NFIX variant there was some evidence of overgrowth consistent with Malan or Marshall-Smith syndrome (183 cm tall, BMI 31.5) but not of intellectual disability (high school education, married), which is a major feature of the syndrome (OMIM# 164005). In the male with GRIA2 variant who died of acute respiratory failure we noted that respiratory dysfunction such as central sleep apnea may be a feature of the associated syndrome (OMIM# 138247) [18]. In the remaining cases there were no data to corroborate the genetic diagnosis. Conversely, in the male with the BRPF1 variant who died at age 45 years from an unknown cause we noted evidence (university level education, married, reasonable income) against the expected intellectual impairment (OMIM#602410).

Other Rare Mendelian Disorders with Relatively High Penetrance

In 12 (9%) respondents we found variants indicating rare Mendelian diseases with relatively high penetrance that did not form a distinct group (Table 1, MD). The most relevant findings included a pathogenic HTT expansion to 68 CAG repeats in a female who died at age 39 years from Huntington disease and a LOF TEK variant predicted to cause venous malformations (OMIM#600221) in a male who died at 49 years from stroke. Notably, he also had hypertension (RR 140/88) perhaps linked to VUS affecting the fifth base of a donor splice site in PKD1. Predisposition to vascular malformations (EPHB4, OMIM#600011, COL4A2, OMIM#120090) was also found in 2 other males who died at ages 30 and 54 years, in an accident or from an unknown cause, respectively.
Other findings, all in persons with an unknown COD, included a PDYN variant associated with relatively late-onset spinocerebellar ataxia 23 (OMIM#610245), a mosaic LOF variant in TBC1D8B (Nephrotic syndrome type 20, OMIM#301027, XL) in a male with apparently severe hypertension (RR 173/105) consistent with kidney disease, a homozygous IL36RN variant well documented to cause a severe form of psoriasis (pustular psoriasis, OMIM# 605507), and a FGFR2 variant linked to Crouzon-like dysostosis (OMIM#176943).
In 4 respondents, 2 of whom died from cancer, 1 from liver cirrhosis and 1 from an accident, we found P/LP variants in genes whose contribution to death was unlikely - MIB1 (Left ventricular non-compaction, OMIM#608677), GPR179 (Night blindness autosomal recessive, OMIM# 614515), EYA1 (Branchiootic syndrome 1 OMIM#601653) and FBN1 (Marfan syndrome, OMIM#134797), respectively.

Low Penetrance Variants/Risk Factors

In 11 (8.7%) respondents we found variants classified as low-penetrance or as risk factors (Table 1, RF). For two variants the plausibility of contributing to the death was assessed as moderate. These included a FOXA3 variant linked with obesity [19] in an overweight male (BMI 26.4, cholesterol 286, triglycerides 241) who died at age 50 years from a CVD and a KITLG variant associated with age-related autosomal dominant deafness 69 (OMIM# 184745) in a male who died at age 47 years in an accident. In the remaining cases the plausibility of contribution of the detected variant(s) to the COD was low or none. The phenotypes associated with the variants were as follows: age-related autosomal dominant deafness (2 cases: MYO7A, MYO6), cystinuria (2 cases, monoallelic SLC7A9 and SLC3A1 variants), obesity, porphyria, Alzheimer disease, pancreatitis (monoallelic variants in POMC, UROD, ABCA7, CTRC, respectively) and hemochromatosis (likely biallelic HFE variants).

Copy Number Variants (CNV)

In three respondents we found structural variants. Interestingly, in two respondents, these were deletions of approximately 0.5 Mb localized in the 22q11.2 DiGeorge deletion region. Although the deletions did not include the TBX1 gene responsible for the core manifestations of the syndrome, one corresponded to a distal 22q11.2 deletion (OMIM# 611867) and the other to a nested "central" deletion located between LCR22-C and LCR22-D (known as a CDdel) [20].
The distal DiGeorge region deletion was found in an unmarried male who died at 51 years from an unknown cause. He reported basic vocational education and a relatively low net monthly income. The distal DiGeorge region deletion is associated with numerous morbidities, although the phenotype is variable (OMIM# 611867). The apparently identical deletion has gnomAD frequency of 0.0088% (11/125,582).
The CDdel in 22q11.2 was found in a female who died at 52 years from non-allergic asthma. Although the CDdel does not cause the full DiGeorge syndrome phenotype, it has been associated with abnormal immune regulation and frequent infections [20,21] which may be relevant to COD.
The 3rd CNV is the already mentioned dup (8)(p22-p21.3) (see Cancer Predisposition).

Novel Candidate Gene-Disease Associations

A hemizygous variant abolishing the start codon of EOLA2 was found in a male with features of metabolic syndrome (BMI 30, RR 142/92, cholesterol 295, triglycerides 412, glucose 101 mg/dL) who died at 49 years from an unknown cause. EOLA2 (endothelium and lymphocyte associated ASCH domain 2) is a poorly characterized gene expressed in mitochondria (www.ncbi.nlm.nih.gov/gene/?term=541578).
A LOF ARID4A variant was found in a male with basic vocational training (3), unmarried, unspecified income who died at 33 years from an unknown cause. While ARID4A is not currently linked to any disease, it is sensitive to monoallelic LOF (pLI = 1). A different ARID4A LOF variant (de novo) was proposed to cause a neurodevelopmental disorder [22] whereas another LOF variant is classified in ClinVar as LP for multiple myeloma (Variation ID: 800352) which is broadly consistent with the hematopoietic phenotype observed in knock-out mice (informatics.jax.org).

Discussion

The main finding from our study is the high (~40%, 31% after exclusion of risk factors and speculative findings) prevalence of reportable results in our PAD population sample. Although this proportion appears high, it is compatible with estimates from genomic studies of unselected adults which identify potentially relevant findings in approximately 20–25% of individuals, with rates approaching one-third when reduced-penetrance variants are included [23,24,25,26,27,28]. These findings support the conclusion that molecular autopsy in PAD is indicated and, given the diversity of findings, it should be performed with a broad, agnostic approach such as ES or genome sequencing.
The prevalence of P/LP variants in genes from the ACMG secondary findings list was relatively high in our cohort (~10%) but it was not significantly different from that observed in the internal reference group of 1,000 Polish adults. However, when variants in cancer-predisposition genes were considered separately a trend (p=0.065) toward an association with PAD emerged. Further support for this association was provided by cause-of-death data, which showed significantly greater concordance with genetic findings (p=0.035) for cancer genes than the other genes on the ACMG list. Interestingly, the dominant role of oncogenic genes in shortening human lifespan is fully consistent with recent large studies in UK [29,30].
The high rate of all reportable findings contrasts with a lower frequency (7%) of findings strongly linked with COD; cancer-predisposition variants accounted for 7/9 of these findings. While this further supports the strong contribution of genetic cancer predisposition to PAD [29,30] it is also consistent with emerging evidence for substantial incomplete penetrance and variable expressivity of many Mendelian diseases [31,32].
However, potential bias should also be considered because cancer provides relatively straightforward genotype–COD concordance, whereas assigning causality is more difficult for variants associated with other diseases. Furthermore, cancer diagnosis is probably easier and more likely to be accepted as COD than other diseases. In non-cancer conditions, symptoms may be elusive and the link with COD may be indirect albeit potentially important, for example for family members. Notably, a recent study emphasized that adult carriers of rare damaging variants predicting neurodevelopmental diseases had measurably poorer cognitive and socioeconomic outcomes despite lacking a classical severe syndrome [32].
In 5 (3.9%) persons we found variants suggesting candidate novel/emerging gene-disease associations. Relevance of candidate novel gene-disease links detected by ES is well known [33] and further justifies an exome-/genome-wide approach in molecular autopsy.
In a participant who died from esophageal cancer, we found the KCNQ1 Arg259His variant, which is associated with cardiac arrhythmias (mainly long- and short-QT syndromes, ClinVar). Interestingly, there is evidence that KCNQ1 may act as a tumor-suppressor gene, particularly in gastrointestinal cancers. In mice, loss of Kcnq1 enhanced tumor formation and progression whereas in human colorectal cancer, reduced KCNQ1 expression predicted poorer survival and higher recurrence risk [34,35]. These effects may be related to the role of KCNQ1 in the Wnt/β-catenin pathway, with its loss causing oncogenic cellular phenotypes [36,37].
A participant who died from lung/bronchial cancer had a heterozygous variant in DROSHA (p.Arg295Ter) predicted to severely truncate the protein. Although DROSHA is not an established cancer gene, its function in microRNA biogenesis makes it an interesting candidate. Furthermore, rare germline LOF DROSHA variants have been linked to pineoblastoma, Wilms tumor and possibly Ewing sarcoma [38] as well as breast cancer [39]; a relatively frequent intronic variant (rs78393591) was implicated in breast cancer by an association study in African women [40].
A third possible novel cancer-predisposition gene is LZTS1, which may have been disrupted in a carrier of ~2.3 Mb dup (8)(p22-p21.3) who died from lung/bronchial cancer. Although the pathogenicity of this variant is unknown, it is intriguing that one of the duplication breakpoints maps within LZTS1, which is a tumor suppressor with a possible role in lung cancer tumorigenesis (www.cancer-genetics.org/LZTS1.htm) [41]. Since the evidence for the tumor-suppressive function of LZTS1 so far has been based only on somatic mutations (www.cancer-genetics.org/LZTS1.htm, OMIM#606551), our case may be the first to suggest a germline effect. The remaining potentially novel candidate genes included EOLA2 and ARID4A, which may be implicated in disorders with metabolic or neurodevelopmental features, respectively.

Conclusions

Exome sequencing of premature adult death in Polish population revealed a high and diverse yield of clinically reportable findings, with cancer-predisposition genes accounting for a substantial proportion of variants most strongly linked to the recorded cause of death.

Acknowledgement

This work was supported by the National Science Centre, Poland (grant no. 2013/11/B/NZ7/04944).

References

  1. Winkel, B.G.; Larsen, M.K.; Berge, K.E.; Leren, T.P.; Nissen, P.H.; Olesen, M.S.; Hollegaard, M.V.; Jespersen, T.; Yuan, L.; Nielsen, N.; Haunsø, S.; Svendsen, J.H.; Wang, Y.; Kristensen, I.B.; Jensen, H.K.; Tfelt-Hansen, J.; Banner, J. The prevalence of mutations in KCNQ1, KCNH2, and SCN5A in an unselected national cohort of young sudden unexplained death cases. J. Cardiovasc. Electrophysiol. 2012, 23, 1092–1098. [Google Scholar] [CrossRef] [PubMed]
  2. Guo, L.; Torii, S.; Fernandez, R.; Braumann, R.E.; Fuller, D.T.; Paek, K.-H.; Gadhoke, N.V.; Maloney, K.A.; Harris, K.; Mayhew, C.M.; Zarpak, R.; Stevens, L.M.; Gaynor, B.J.; Jinnouchi, H.; Sakamoto, A.; Sato, Y.; Mori, H.; Kutyna, M.D.; Lee, P.J.; Weinstein, L.M.; Collado-Rivera, C.J.; Ali, B.B.; Atmakuri, D.R.; Dhingra, R.; Finn, E.L.B.; Bell, M.W.; Lynch, M.; Cornelissen, A.; Kuntz, S.H.; Park, J.-H.; Kutys, R.; Park, J.-E.; Wang, L.; Hong, S.N.; Gupta, A.; Hall, J.L.; Kolodgie, F.D.; Romero, M.E.; Jeng, L.J.B.; Mitchell, B.D.; Surve, D.; Fowler, D.R.; Hong, C.C.; Virmani, R.; Finn, A.V. Genetic variants associated with unexplained sudden cardiac death in adult White and African American individuals. JAMA Cardiol. 2021, 6, 1013–1022. [Google Scholar] [CrossRef] [PubMed]
  3. Anderson, J.H.; Tester, D.J.; Will, M.L.; Ackerman, M.J. Whole-exome molecular autopsy after exertion-related sudden unexplained death in the young. Circ. Cardiovasc. Genet. 2016, 9, 259–265. [Google Scholar] [CrossRef] [PubMed]
  4. Khera, A.V.; Chaffin, M.; Zekavat, S.M.; Collins, R.L.; Roselli, C.; Natarajan, P.; Lichtman, J.H.; D'Onofrio, G.; Mattera, J.; Dreyer, R.; Spertus, J.A.; Taylor, K.D.; Psaty, B.M.; Rich, S.S.; Post, W.; Gupta, N.; Gabriel, S.; Lander, E.; Chen, Y.-D.I.; Talkowski, M.E.; Rotter, J.I.; Krumholz, H.M.; Kathiresan, S. Whole-genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction. Circulation 2019, 139, 1593–1602. [Google Scholar] [CrossRef] [PubMed]
  5. Noebels, J.L. Genetic and cellular mechanisms underlying SUDEP risk. In Jasper’s Basic Mechanisms of the Epilepsies, 5th ed.; Noebels, J.L., Avoli, M., Rogawski, M.A., Vezzani, A., Delgado-Escueta, A.V., Eds.; Oxford University Press: Oxford, UK, 2024; p. Chapter 63. [Google Scholar] [CrossRef] [PubMed]
  6. Nakano, Y.; Shimizu, W. Syncope in patients with inherited arrhythmias. J. Arrhythm. 2017, 33, 572–578. [Google Scholar] [CrossRef] [PubMed]
  7. Chang, Z.; Lichtenstein, P.; D’Onofrio, B.M.; Sjölander, A.; Larsson, H. Serious transport accidents in adults with attention-deficit/hyperactivity disorder and the effect of medication: A population-based study. JAMA Psychiatry 2014, 71, 319–325. [Google Scholar] [CrossRef] [PubMed]
  8. Mirkovic, B.; Laurent, C.; Podlipski, M.A.; Frebourg, T.; Cohen, D.; Gerardin, P. Genetic association studies of suicidal behavior: A review of the past 10 years, progress, limitations, and future directions. Front. Psychiatry 2016, 7, 158. [Google Scholar] [CrossRef] [PubMed]
  9. Mullins, N.; Perroud, N.; Uher, R.; Butler, A.W.; Cohen-Woods, S.; Rivera, M.; Malki, K.; Euesden, J.; Power, R.A.; Tansey, K.E.; Jones, L.; Jones, I.; Craddock, N.; Owen, M.J.; Korszun, A.; Gill, M.; Mors, O.; Preisig, M.; Maier, W.; Rietschel, M.; Rice, J.P.; Muller-Myhsok, B.; Binder, E.B.; Lucae, S.; Ising, M.; Craig, I.W.; Farmer, A.E.; McGuffin, P.; Breen, G.; Lewis, C.M. Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: A genome-wide association and polygenic scoring study. Am. J. Med. Genet. B Neuropsychiatr. Genet. 2014, 165B, 428–437. [Google Scholar] [CrossRef] [PubMed]
  10. Rywik, S.; Kupsc, W.; Piotrowski, W.; Broda, G. Multi-Center All-Polish Health Survey—WOBASZ Project. Methodological assumptions and logistics. Pol. Popul. Rev. 2005, 27, 37–50. [Google Scholar]
  11. Miller, D.T.; Lee, K.; Chung, W.K.; Gordon, A.S.; Herman, G.E.; Klein, T.E.; Stewart, D.R.; Amendola, L.M.; Adelman, K.; Bale, S.J.; Gollob, M.H.; Harrison, S.M.; Hershberger, R.E.; McKelvey, K.; Richards, C.S.; Vlangos, C.N.; Watson, M.S.; Martin, C.L. ACMG Secondary Findings Working Group. ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: A policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet. Med. 2021, 23, 1381–1390. [Google Scholar] [CrossRef] [PubMed]
  12. Śmigiel, R.; Biela, M.; Szmyd, K.; Błoch, M.; Szmida, E.; Skiba, P.; Walczak, A.; Gasperowicz, P.; Kosińska, J.; Rydzanicz, M.; Stawiński, P.; Biernacka, A.; Zielińska, M.; Gołębiowski, W.; Jalowska, A.; Ohia, G.; Głowska, B.; Walas, W.; Królak-Olejnik, B.; Krajewski, P.; Sykut-Cegielska, J.; Sąsiadek, M.M.; Płoski, R. Rapid whole-exome sequencing as a diagnostic tool in a neonatal/pediatric intensive care unit. J. Clin. Med. 2020, 9, 2220. [Google Scholar] [CrossRef] [PubMed]
  13. Fowler, A.; Mahamdallie, S.; Ruark, E.; Seal, S.; Ramsay, E.; Clarke, M.; Uddin, I.; Wylie, H.; Strydom, A.; Lunter, G.; Rahman, N. Accurate clinical detection of exon copy number variants in a targeted NGS panel using DECoN. Wellcome Open Res. 2016, 1, 20. [Google Scholar] [CrossRef] [PubMed]
  14. Talevich, E.; Shain, A.H.; Botton, T.; Bastian, B.C. CNVkit: Genome-wide copy number detection and visualization from targeted DNA sequencing. PLoS Comput. Biol. 2016, 12, e1004873. [Google Scholar] [CrossRef] [PubMed]
  15. Stawiński, P.; Płoski, R. Genebe.net: Implementation and validation of an automatic ACMG variant pathogenicity criteria assignment. Clin. Genet. 2024, 106, 119–126. [Google Scholar] [CrossRef] [PubMed]
  16. Richards, S.; Aziz, N.; Bale, S.; Bick, D.; Das, S.; Gastier-Foster, J.; Grody, W.W.; Hegde, M.; Lyon, E.; Spector, E.; Voelkerding, K.; Rehm, H.L.; ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: A joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 2015, 17, 405–424. [Google Scholar] [CrossRef] [PubMed]
  17. Tavtigian, S.V.; Harrison, S.M.; Boucher, K.M.; Biesecker, L.G. Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines. Hum. Mutat. 2020, 41, 1734–1737. [Google Scholar] [CrossRef] [PubMed]
  18. Sjøstrøm, E.; Studniarczyk, D.; Dou, X.; Dahl, R.S.; Cruz, V.; Wang, H.; Mercier, S.; Deb, W.; Besnard, T.; Friedman, J.; Essid, M.; Karoui, S.; Ben Jemaa, L.; Benyounes, T.; Lesca, G.; Tonduti, D.; Iascone, M.; Orcesi, S.; Fradin, M.; Dubourg, C.; Napuri, S.; Cull-Candy, S.G.; Coombs, I.D.; Farrant, M.; Bayat, A. Clinical and neurodevelopmental characteristics of paralogous gain-of-function variants at GRIA2 p.Gly792 and GRIA3 p.Gly803. Clin. Genet. 2025, 108, 553–565. [Google Scholar] [CrossRef] [PubMed]
  19. Adler-Wailes, D.C.; Alberobello, A.T.; Ma, X.; Hugendubler, L.; Stern, E.A.; Mou, Z.; Han, J.C.; Kim, P.W.; Sumner, A.E.; Yanovski, J.A.; Mueller, E. Analysis of variants and mutations in the human winged helix FOXA3 gene and associations with metabolic traits. Int. J. Obes. 2015, 39, 888–892. [Google Scholar] [CrossRef] [PubMed]
  20. Bertini, V.; Cambi, F.; Legitimo, A.; Costagliola, G.; Consolini, R.; Valetto, A. 22q11.21 deletions: A review on the interval mediated by low-copy repeats C and D. Genes 2025, 16, 72. [Google Scholar] [CrossRef] [PubMed]
  21. Soares, D.C.Q.; Dutra, R.L.; Quaio, C.R.D.C.; Melaragno, M.I.; Kulikowski, L.D.; Torres, L.C.; Kim, C.A. Role of SNAP29, LZTR1 and P2RXL1 genes on immune regulation in a patient with atypical 0.5 Mb deletion in 22q11.2 region. Clin. Immunol. 2012, 145, 55–58. [Google Scholar] [CrossRef] [PubMed]
  22. Ormieres, C.; Lesieur-Sebellin, M.; Siquier-Pernet, K.; Delplancq, G.; Rio, M.; Parisot, M.; Nitschké, P.; Rodriguez-Fontenla, C.; Bodineau, A.; Narcy, L.; Schlumberger, E.; Cantagrel, V.; Malan, V. Deciphering the genetic basis of developmental language disorder in children without intellectual disability, autism or apraxia of speech. Mol. Autism 2025, 16, 10. [Google Scholar] [CrossRef] [PubMed]
  23. Rego, S.; Dagan-Rosenfeld, O.; Zhou, W.; Sailani, M.R.; Limcaoco, P.; Colbert, E.; Avina, M.; Wheeler, J.; Craig, C.; Salins, D.; Röst, H.L.; Dunn, J.; McLaughlin, T.; Steinmetz, L.M.; Bernstein, J.A.; Snyder, M.P. High-frequency actionable pathogenic exome variants in an average-risk cohort. Cold Spring Harb. Mol. Case Stud. 2018, 4, a003178. [Google Scholar] [CrossRef] [PubMed]
  24. Machini, K.; Ceyhan-Birsoy, O.; Azzariti, D.R.; Sharma, H.; Rossetti, P.; Mahanta, L.; Hutchinson, L.; McLaughlin, H.; MedSeq Project; Green, R.C.; Lebo, M.; Rehm, H.L. Analyzing and reanalyzing the genome: Findings from the MedSeq Project. Am. J. Hum. Genet. 2019, 105, 177–188. [Google Scholar] [CrossRef] [PubMed]
  25. Hou, Y.C.C.; Yu, H.C.; Martin, R.; Cirulli, E.T.; Schenker-Ahmed, N.M.; Hicks, M.; Cohen, I.V.; Jönsson, T.J.; Heister, R.; Napier, L.; Swisher, C.L.; Dominguez, S.; Tang, H.; Li, W.; Perkins, B.A.; Barea, J.; Rybak, C.; Smith, E.; Duchicela, K.; Doney, M.; Brar, P.; Hernandez, N.; Kirkness, E.F.; Kahn, A.M.; Venter, J.C.; Karow, D.S.; Caskey, C.T. Precision medicine integrating whole-genome sequencing, comprehensive metabolomics, and advanced imaging. Proc. Natl. Acad. Sci. USA 2020, 117, 3053–3062. [Google Scholar] [CrossRef] [PubMed]
  26. Cochran, M.; East, K.; Greve, V.; Kelly, M.; Kelley, W.; Moore, T.; Myers, R.M.; Odom, K.; Schroeder, M.C.; Bick, D. A study of elective genome sequencing and pharmacogenetic testing in an unselected population. Mol. Genet. Genom. Med. 2021, 9, e1766. [Google Scholar] [CrossRef] [PubMed]
  27. Wildin, R.S.; Gerrard, D.L.; Leonard, D.G.B. Real-world results from combined screening for monogenic genomic health risks and reproductive risks in 300 adults. J. Pers. Med. 2022, 12, 1962. [Google Scholar] [CrossRef] [PubMed]
  28. Linderman, M.D.; Adelson, S.M.; Berro, T.M.; Anderson, J.L.; Crawford, S.D.; Cunningham, T.J.; Esplin, E.D.; Ewing-Crawford, A.T.; Nielsen, D.E.; Pereira, S.; Schmidlen, T.; Andrighetti, H.; Bleyl, S.B.; Church, G.M.; Haverfield, E.V.; Hegde, M.; Konstantinos, L.N.; Kruszka, P.; Leonard, D.; May, T.; McGinniss, M.; Pandya, V.; Schadt, E.E.; Greshake Tzovaras, B.; Zettler, B.; McGuire, A.L.; Green, R.C.; PeopleSeq Study Team. Elective genomic sequencing for adults in research, clinical and commercial contexts. BMC Med. Genom. 2026. [Google Scholar] [CrossRef] [PubMed]
  29. Liu, J.Z.; Chen, C.Y.; Tsai, E.A.; Whelan, C.D.; Sexton, D.; John, S.; Runz, H. The burden of rare protein-truncating genetic variants on human lifespan. Nat. Aging 2022, 2, 289–294. [Google Scholar] [CrossRef] [PubMed]
  30. Park, J.; Peña-Tauber, A.; Talozzi, L.; Greicius, M.D.; Le Guen, Y. Rare genetic associations with human lifespan in UK Biobank are enriched for oncogenic genes. Nat. Commun. 2025, 16, 2064. [Google Scholar] [CrossRef] [PubMed]
  31. Forrest, I.S.; Chaudhary, K.; Vy, H.M.T.; Petrazzini, B.O.; Bafna, S.; Jordan, D.M.; Rocheleau, G.; Loos, R.J.F.; Nadkarni, G.N.; Cho, J.H.; Do, R. Population-based penetrance of deleterious clinical variants. JAMA 2022, 327, 350–359. [Google Scholar] [CrossRef] [PubMed]
  32. Kingdom, R.; Tuke, M.; Wood, A.; Beaumont, R.N.; Frayling, T.M.; Weedon, M.N.; Wright, C.F. Rare genetic variants in genes and loci linked to dominant monogenic developmental disorders cause milder related phenotypes in the general population. Am. J. Hum. Genet. 2022, 109, 1308–1316. [Google Scholar] [CrossRef] [PubMed]
  33. Farwell Hagman, K.D.; Shinde, D.N.; Mroske, C.; Smith, E.; Radtke, K.; Shahmirzadi, L.; El-Khechen, D.; Powis, Z.; Chao, E.C.; Alcaraz, W.A.; Helbig, K.L.; Sajan, S.A.; Rossi, M.; Lu, H.-M.; Huether, R.; Li, S.; Wu, S.; Nuñes, M.E.; Tang, S. Candidate-gene criteria for clinical reporting: Diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases. Genet. Med. 2017, 19, 224–235. [Google Scholar] [CrossRef] [PubMed]
  34. Than, B.L.N.; Goos, J.A.C.M.; Sarver, A.L.; O'Sullivan, M.G.; Rod, A.; Starr, T.K.; Fijneman, R.J.A.; Meijer, G.A.; Zhao, L.; Zhang, Y.; Largaespada, D.A.; Scott, P.M.; Cormier, R.T. The role of KCNQ1 in mouse and human gastrointestinal cancers. Oncogene 2014, 33, 3861–3868. [Google Scholar] [CrossRef] [PubMed]
  35. den Uil, S.H.; Coupé, V.M.H.; Linnekamp, J.F.; van den Broek, E.; Goos, J.A.C.M.; Delis-van Diemen, P.M.; Belt, E.J.T.; van Grieken, N.C.T.; Scott, P.M.; Vermeulen, L.; Medema, J.P.; Bril, H.; Stockmann, H.B.A.C.; Cormier, R.T.; Meijer, G.A.; Fijneman, R.J.A. Loss of KCNQ1 expression in stage II and stage III colon cancer is a strong prognostic factor for disease recurrence. Br. J. Cancer 2016, 115, 1565–1574. [Google Scholar] [CrossRef] [PubMed]
  36. Rapetti-Mauss, R.; Bustos, V.; Thomas, W.; McBryan, J.; Harvey, H.; Lajczak, N.; Madden, S.F.; Pellissier, B.; Borgese, F.; Soriani, O.; Harvey, B.J. Bidirectional KCNQ1:β-catenin interaction drives colorectal cancer cell differentiation. Proc. Natl. Acad. Sci. USA 2017, 114, 4159–4164. [Google Scholar] [CrossRef] [PubMed]
  37. Berenguier, C.; Chen, X.; Allegrini, B.; Guizouarn, H.; Borgese, F.; Etchebest, C.; Soriani, O.; Rapetti-Mauss, R. Cancer-associated loss-of-function mutations in KCNQ1 enhance Wnt/β-catenin signalling disrupting epithelial homeostasis. Oncogene 2025, 44, 2715–2729. [Google Scholar] [CrossRef] [PubMed]
  38. Fiorica, P.N.; Golmard, L.; Kim, J.; Bao, R.; Lin, F.Y.; Roy, A.; Pribnow, A.; Perrino, M.R.; Masliah-Planchon, J.; Michalak-Provost, S.; Wong, J.; Filser, M.; Stoppa-Lyonnet, D.; Bourdeaut, F.; Brahimi, A.; Ingster, O.; Saulnier Sholler, G.; Jackson, S.A.; Sasaki, M.M.; Fowler, T.; Ng, A.; Corbett, R.J.; Kaufman, R.S.; Haley, J.S.; Carey, D.J.; Huang, K.-L.; Diskin, S.J.; Rokita, J.L.; Al-Kateb, H.; McGee, R.B.; Schiffman, J.D.; Chen, K.S.; Stewart, D.R.; Parsons, D.W.; Plon, S.E.; Schultz, K.A.P.; Onel, K. Germline pathogenic DROSHA variants are linked to pineoblastoma and Wilms tumor predisposition. Clin. Cancer Res. 2025, 31, 1491–1503. [Google Scholar] [CrossRef] [PubMed]
  39. Felicio, P.S.; Grasel, R.S.; Campacci, N.; de Paula, A.E.; Galvão, H.C.R.; Torrezan, G.T.; Sabato, C.S.; Fernandes, G.C.; Souza, C.P.; Michelli, R.D.; Andrade, C.E.; Barros, B.D.D.F.; Matsushita, M.M.; Revil, T.; Ragoussis, J.; Couch, F.J.; Hart, S.N.; Reis, R.M.; Melendez, M.E.; Tonin, P.N.; Carraro, D.M.; Palmero, E.I. Whole-exome sequencing of non-BRCA1/BRCA2 mutation carrier cases at high-risk for hereditary breast/ovarian cancer. Hum. Mutat. 2021, 42, 290–299. [Google Scholar] [CrossRef] [PubMed]
  40. Qian, F.; Feng, Y.; Zheng, Y.; Ogundiran, T.O.; Ojengbede, O.; Zheng, W.; Blot, W.; Ambrosone, C.B.; John, E.M.; Bernstein, L.; Hu, J.J.; Ziegler, R.G.; Nyante, S.; Bandera, E.V.; Ingles, S.A.; Press, M.F.; Nathanson, K.L.; Hennis, A.; Nemesure, B.; Ambs, S.; Kolonel, L.N.; Olopade, O.I.; Haiman, C.A.; Huo, D. Genetic variants in microRNA and microRNA biogenesis pathway genes and breast cancer risk among women of African ancestry. Hum. Genet. 2016, 135, 1145–1159. [Google Scholar] [CrossRef] [PubMed]
  41. Toyooka, S.; Fukuyama, Y.; Wistuba, I.I.; Tockman, M.S.; Minna, J.D.; Gazdar, A.F. Differential expression of FEZ1/LZTS1 gene in lung cancers and their cell cultures. Clin. Cancer Res. 2002, 8, 2292–2297. [Google Scholar] [PubMed]
Table 1. Pathogenic (P)/likely pathogenic (LP) variants found in studied individuals.
Table 1. Pathogenic (P)/likely pathogenic (LP) variants found in studied individuals.
Person ID Sex Cause of death Genetic finding
category		 Variant (Protein/RNA) Zygosity ACMG(points), criteria; ClinVar Disease Effect Comments Plausibility
465 M ? Ca NR-COD NM_020937.4(FANCM):c.1972C>T (p.Arg658*) het. P(17)PVS1,PS3_str, PM2_sup, PP5_str.; ClinVar: P 11 Cancer AD (weak risk factor) According to ClinVar: "This variant has been observed to be heterozygous in individuals affected with ovarian cancer, polycythemia vera, and breast cancer (PMID: 21681190, 26822949, 29351780, 29287190, 28033443, 28881617); and in a large case-control study, this variant was observed more frequently in individuals with ER-negative breast cancer (OR=2.44, 95% CI [1.12-5.34], p=0.034) or triple-negative breast cancer (OR=3.79, 95% CI [1.56-9.18], p=0.009) than among controls (PMID: 31700994)." Low
467 M CVD Ca NR-COD NM_000465.4(BARD1):c.1690C>T (p.Gln564*) het. P(18)PVS1,PS3_str, PM2_mod, PP5_str; ClinVar: P 31 Cancer, OMIM#114480 AD (risk factor) None
640 F cancer Ca NM_004972.4(JAK2):c.2105T>G (p.Ile702Ser) het. LP(8)PM1,PM2, PP3_str

 Hematological malignancy OMIM#147796 AD death at 53 years, 7 years after WOBASZ examination, no evidence for mosaicism, variant present in 43% (17/40) reads High
644 F ? MD NM_024411.5(PDYN):c.643C>T (p.Arg215Cys) het. LP(6)PS3_sup,PM2_sup, PP3_mod, PP5_mod; ClinVar: P 1 Spinocerebellar ataxia 23 OMIM#610245 AD Death at 44 years, high school education (5), married, income per family member 301 -500 zl. Variant association with disease described in PMID: 21035104, functional study: PMID: 21712028 Moderate
648 M liver cirrhosis MD NM_000503.6(EYA1):c.202+1G>A het. P(10),PVS1_mod,PS1_str, PM2_mod,PP5_mod; ClinVar: P 1 Branchiootic syndrome 1 OMIM#601653 AD Death at 51 years, 170 cm, 78 kg, basic vocational education (3), married, income per family member 1 (<300 zl), RR 123/80 mmHg, alk.consumption - 42.65 Low
654 M ? CVD, ACMG_CVD NM_000256.3(MYBPC3):c.175A>G (p.Thr59Ala) het. ACMG list CVD; ClinVar: P 1 Cardiomyopathy/Left ventricular noncompaction OMIM#600958 AD ACMG list CVD Moderate
655 M alcohol-related mental/ behavioral disorders RF NM_000939.4(POMC):c.251G>A (p.Trp84Ter) het. LP(7) PVS1_str, PM2_sup,PP5_mod; ClinVar: P 2 Obesity, OMIM# 601665 AD (risk factor) BMI 23.4, None
656 F breast cancer Ca, ACMG_Ca NM_007294.4(BRCA1):c.5266dup (p.Gln1756ProfsTer74) het. P(17)PVS1_str,PS3, PM2_sup, PP5_v_str.; ClinVar: P:93 U:1 O:3 Ca {Breast-ovarian cancer, familial, 1} OMIM#113705 AD ACMG list Ca High
658 F lung/bronchial cancer CNV Ca possible defect of LZTS1. Includes ASAH1, ATP6V1B2, CSGALNACT1, INTS10, LPL, LZTS1, NAT1, NAT2, PCM1 PSD3 SH2D4A SLC18A1 het. VUS (CNV) Esophageal squamous cell carcinoma, somatic, OMIM#606551 AD LZTS1 may be a tumor suppressor according to www.cancer-genetics.org/LZTS1.htm. PMID: 12114433 concluded that FEZ1 (now known as LZTS1) may be related to tumorigenesis of lung cancer based on expression studies. Low speculative
662 F liver cirrhosis RF NM_000260.4(MYO7A):c.1369G>A (p.Ala457Thr) het. LP(7)PM1,PM2,PM5,PP5; ClinVar: P:1 U:2 Deafness, autosomal dominant 11 OMIM#276903 AD Associated with dominant sensorineural hearing loss/late-onset in PMID:34824372, 38594301 None
663 F oral cancer Ca NM_002878.4(RAD51D):c.451C>T (p.Gln151Ter) het. P(13)PVS1,PM2_sup, PP5_str; ClinVar: P:14 {Breast-ovarian cancer, familial, susceptibility to, 4} AD High
668 M ? ND NM_001003694.2(BRPF1):c.2636-2A>G het. LP(6),PVS1, PM2; ClinVar: absent, but 3 P LOF variants downstream in the same exon. Intellectual developmental disorder with dysmorphic facies and ptosis OMIM#602410 AD Death at 45 years, 180 cm. 79 kg, (university) education (8), married, income per family member -500-700 zl (3). Evidence for substantial intrafamilial variability with presence of pathogenic variants in relatively mildly affected adults (PMID: 27992417, PMID: 31020800). Low
669 M ? Novel NM_001013845.2(EOLA2):c.2T>A (p.Met1?) hemizygous LP(6)PVS1_str (downstream start codon present, truncates > 10% of CDS), PM2 Novel disease? XLR? death at 49 years, BMI 30, RR 142/92, glucose 101 mg/dL. cholesterol 295 triglycerides 412 Low speculative
671 M ? MD NM_001846.4(COL4A2):c.3882_3891dup (p.Pro1298SerfsTer18) het. P(12)PVS1,PM2, PP5_mod; ClinVar: P:1 Brain small vessel disease 2A, autosomal dominant OMIM#120090 AD Death at 54 years, BMI = 26, RR 156/97 Moderate
672 F traffic accident Ca NR-COD NM_000548.5(TSC2):c.5260-9_5279del het. P(14)PVS1,PS1,PM2; ClinVar: U:3 Tuberous sclerosis-2 OMIM#191092 AD Evidence for incomplete penetrance PMID: 42151584 Moderate
713 F ? Ca NR-COD NM_006767.4(LZTR1):c.604_605delAT (p.Met202ValfsTer57) het P(13)PVS1,PM2_ sup., PP5 str.; ClinVar: P:5 Schwannomatosis-2, susceptibility to OMIM#600574 AD (risk factor) Low
714 F ? MD NM_012275.3(IL36RN):c.338C>T (p.Ser113Leu) hom. P(8)PS3,PP5 str; ClinVar: P:14 U:2 O:1 Psoriasis 14, pustular OMIM#605507 AR Considerable evidence for pathogenicity in literature PMID: 21839423, 23428889, 37414245, 27388993, 25989471, 25427108, 29030861, 23303454, 27220475 Moderate
715 F ovarian cancer Ca, ACMG_Ca NM_000059.4(BRCA2):c.6136delT (p.Ser2046HisfsTer5) het. P(18)PVS1,PM2,PP5_v.str; ClinVar: P:2 {Breast-ovarian cancer, familial, 2} OMIM# 600185 AD ACMG list Ca High
717 M alcohol-related liver cirrhosis RF NM_014270.5(SLC7A9):c.313G>A (p.Gly105Arg) het. P(20)PS3,PP3_mod, PP5_str.; ClinVar: P:20 Cystinuria, OMIM#604144 AD (risk factor) Individuals with a single pathogenic SLC7A9 variant have symptoms onset at a mean of 30 years (PMID: 25296721). None
718 M ? CVD, ACMG_CVD NM_000257.4(MYH7):c.4498C>T (p.Arg1500Trp) het. P(17)PS3,PM1, PM2, PM5, PP2, PP3_mod., PP5_str.; ClinVar: P:9 Cardiomyopathy OMIM# 160760 AD ACMG list CVD Moderate
734 M CVD (cardiac infarction) Ca NR-COD, ACMG_Ca NM_024675.4(PALB2):c.109-12T>A het. LP(9)PS3,PM2,PP3_mod,PP5; ClinVar: P:7 U:1 Breast-ovarian cancer, familial, susceptibility to, 5; Pancreatic cancer, susceptibility to, 3 OMIM#610355 AD ACMG list Ca None
738 M non-traumatic epidural hemorrhage RF, ACMG_other NM_000410.4(HFE):c.187C>G (p.His63Asp)/ NM_000410.4(HFE):c.845G>A (p.Cys282Tyr) comp. het P(12)PS3_str, PP5_ v_str /PS3, PP3_mod, PP5_str; ClinVar: P:52 U:3 B:1 O:6 / P:50 U:2 B:1 O:6 Hemochromatosis, type 1 OMIM#613609 AR (risk factor) ACMG list other; variants likely in trans, own population data do not support linkage disequilibrium) None
740 M ? MD NM_000141.5(FGFR2):c.943G>T (p.Ala315Ser) het. LP(8)PM1,PM2, PP2, PP5_str, BP4; ClinVar: P:8 Crouzon syndrome, craniosynostosis, numerous other skeletal abnormalities OMIM#176943 AD 194 cm tall, BMI = 16.7, According to PMID: 12357470, 10951518, 28611549, 24127277 the FGFR2 p.Ala315Ser is a pathogenic dominant variant associated with a broad and often mild craniofacial phenotype, ranging from isolated unicoronal craniosynostosis to subtle facial asymmetry or Crouzon-like craniofacial dysostosis without overt craniosynostosis. PMID: 28611549 describes a proband with FGFR2 p.Ala315Ser and Crouzonoid appearance as well as obstructive sleep apnea episodes leading to reduced oxygen saturation. Moderate
741 M ? CVD, ACMG_CVD NM_001943.5(DSG2):c.2620del (p.Thr874LeufsTer29) het. P(11)PVS1,PM2, PP5; ClinVar: P:4 U:3 Cardiomyopathy, OMIM#125671 AD ACMG list CVD Moderate
743 M lung/bronchial cancer Ca/ACMG_CVD NM_001382508.1(DROSHA):c.883C>T (p.Arg295Ter)/NM_003280.3(TNNC1):c.23C>T (p.Ala8Val) het./het. LP(6)PVS1,PM2,BS2/P(12) PS3, PM1, PM2_sup, PP3, PP5_str; ClinVar: P:15, U:1 Cancer?/TNNC1 variant is associated with cardiomyopathy OMIM#191040 AD/AD Germline LOF DROSHA variants may underlie a novel autosomal-dominant predisposition associated with pineoblastoma and Wilms tumor, and possibly Ewing sarcoma (PMID: 39992227). Furthermore, monoallelic pathogenic DROSHA variants were associated with neurodevelopmental disorder in GeneCC (PMID:35405010). /ACMG list CVD Low speculative/none
744 M cancer MD, ACMG_other NM_001004334.4(GPR179):c.984del (p.Ser329LeufsTer4) hom. P(12)PVS1,PP5_str; ClinVar: P:17 Night blindness, congenital stationary (complete), 1E, autosomal recessive OMIM#614515 AR ACMG list other None
746 F cancer MD NM_020774.4(MIB1):c.1092+2T>G het. P(10)PVS1,PM2 Left ventricular noncompaction 7 , OMIM#608677 AD None
748 F cervical cancer Ca, ACMG_Ca NM_000179.3(MSH6):c.3018C>G (p.Tyr1006Ter) /NM_002354.3(EPCAM):c.1A>G (p.Met1?) het. /het P(14)PVS1,PM2,PP5_str/P(15)PVS1,PS1_mod,PM2_sup,PP5_str; ClinVar: P:3 /P3 Lynch syndrome 5 OMIM#600678 /Lynch syndrome 8 OMIM#613244 AD ACMG list Ca, According to PMID: 26077226 the incidence of cervical cancer was 5.6 fold increased in Lynch syndrome patients (95% CI: 2.3-13.8; p = 0.001) vs general population. High/High
752 M CVD RF NM_004497.3(FOXA3):c.731C>T (p.Ala244Val) het. LP(7)PS3(PMID: 25672906), PM2, PP3 Obesity PMID: 25672906 AD (weak risk factor) Death at 50 years, BMI = 26.4, cholesterol 286, triglycerides 241 Moderate
753 M liver cirrhosis ND NM_032607.3(CREB3L3):c.732dup (p.Lys245GlufsTer130) / NM_172107.4(KCNQ2):c.602G>A (p.Arg201His) het./ mosaic - 16% (7/45 reads) LP(8),PVS1/ P (19) PS3, PM1, PM2, PM5, PP2, PP3_str, PP5_str; ClinVar: P:1 U:5 B:1/P7 0:1 CREB3L3: hypertriglyceridaemia 2, OMIM#611998/ KCNQ2: Epilepsy OMIM#602235 AD/AD Death at 41 years, primary education (2), married, income per family member <300zl (1), alcohol consumption 2.75; triglycerides =208 mg/dL (elevated) / incidental 2. variant Low/none
757 F ovarian cancer RF NM_000374.5(UROD):c.616C>T (p.Gln206Ter) het. P(13)PVS1,PM2_sup, PP5_str; ClinVar: P:7 Porphyria OMIM# 613521 AD None
758 F esophageal cancer Ca, ACMG_CVD NM_000218.3(KCNQ1):c.776G>A (p.Arg259His)/ NM_003480.4(MFAP5):c.248-2A>G (mosaic, 6% (7/45) reads) P(18)PS3,PM1,PM2,PM5, PP3_str, PP5_str/ LP(6) PVS1_str, PM2; ClinVar: P:15 O:1 KCNQ1: Long QT syndrome, other cardiac arrhythmias OMIM#607542 /MFAP5: Aortic aneurysm, familial thoracic 9 OMIM#601103 AD/AD ACMG list CVD, see Discussion for possible link of KCNQ1 with cancer Low speculative/None
839 M cancer, unknown origin Ca NM_007194.4(CHEK2):c.470T>C (p.Ile157Thr) het. LP(6)PS3,PP5_mod; ClinVar: P:39 U:11 O:4 Tumor predisposition syndrome 4, OMIM#604373 AD High
842 M ? ND NM_001365902.3(NFIX):c.266_276del (p.Glu89AlafsTer26) het. P(10),PVS1,PM2 Malan syndrome, Marshall-Smith syndrome, OMIM#164005 AD Death at 50 years, high school education (5), married, income =1 (<300 zl /family member), 183 cm tall, BMI 31.5. Moderate
844 M ? Ca NR-COD, ACMG_Ca NM_000059.4(BRCA2):c.6118del (p.Ile2040TyrfsTer11) het. P(10),PVS1,PM2 {Breast-ovarian cancer, familial, 2} OMIM#600185 AD ACMG list Ca Moderate
847 M accident MD, ACMG_CVD NM_000138.5(FBN1):c.494G>A (p.Arg165Gln) het. LP(7),PM1PM2 Sup,PM5,PP2, PP5; ClinVar: P:1 U:2 Marfan syndrome OMIM#134797 AD ACMG list CVD, 169 cm tall Low
849 F ? RF NM_004999.4(MYO6):c.1178_1188dup (p.Thr397GlufsTer4) het. P(10)PVS1,PM2 Deafness, autosomal dominant 22, OMIM# 600970 AD Similar neighboring LOF variant (NM_004999.4(MYO6):c.1159C>T (p.Arg387Ter)) associated in ClinVar with AD hearing loss Low
850 M accident RF NM_019112.4(ABCA7):c.5713-1G>A het. P(10)PVS1,PM2 {Alzheimer disease 9, susceptibility to} OMIM#605414 AD (risk factor) PMID: 25807283 OR ~2 Low
852 M accident RF NM_000341.4(SLC3A1):c.1354C>T (p.Arg452Trp) het. P(11)PM1,PM2_sup,PP3_str, PP5_str; ClinVar: P:7 Cystinuria OMIM#104614 AD (risk factor) None
854 F Huntington disease MD HTT CAG repeat expansion (pathogenic allele: 68 CAG repeats) het. Huntington disease OMIM#613004 AD High
856 M accident Ca NR-COD NM_006767.4(LZTR1):c.769del (p.Gln257SerfsTer94) het. P(10),PVS1,PM2 {Schwannomatosis-2, susceptibility to OMIM#600574 AD (risk factor) None
857 M ? CNV Removes BCR, GGTLC2, GNAZ, IGLL5, RAB36, RSPH14 but not TBX1 het. P score 1 (for CNV) 22q11.2 DiGeorge region deletion, distal, OMIM#611867 AD Death at 51 years, basic vocational education (3), unmarried, income per family member 300-500 zl (2) Moderate
859 F ? ND NM_012309.5(SHANK2):c.602del (p.Leu201ArgfsTer3) het. LP(9),PVS1,PM2_Sup. {Autism susceptibility 17} AD Death at 54 years, post-secondary non-tertiary education (6), widow, income per family member (1) <300zl Low
860 M accident MD NM_004444.5(EPHB4):c.1546G>A (p.Gly516Arg) het. LP(6),PM1,PM2,PP3,PP5(PMID: 28687708) Capillary malformation-arteriovenous malformation 2 OMIM#600011 AD death at 30 years, RR 131/72 Moderate
864 M ? Ca NM_004972.4(JAK2):c.1849G>T (p.Val617Phe) het., mosaic? (38% (15/39) reads) P(14)PS3,PM1, PM5, PP3_mod, PP5_str; ClinVar: P:28 O:2 Thrombocythemia 3, hematological malignancy (somatic) OMIM#147796 AD High
868 M CVD RF NM_007272.3(CTRC):c.738_761del (p.Lys247_Arg254del) het. P(12),PS3,PM1_sup, PM2_sup, PM4, PP5_str; ClinVar: P:7 O:2 {Pancreatitis, chronic, susceptibility to} OMIM#601405 AD (risk factor) Additional finding, 4:154584300-A>T, NM_000508.5(FGA):c.2425T>A (p.Tyr809Asn) VUS FGA None
870 M ? MD NM_017752.3(TBC1D8B):c.1030C>T (p.Arg344Ter) mosaic, 38% (8/21) reads LP(8),PVS1, ClinVar: P:1 U:1 Nephrotic syndrome, type 20, OMIM#301027 XL Death at 50 years, RR 173/105, BMI 27.6, diabetes. The variant was described as pathogenic in a hemizygous male (PMID: 31732614). Evidence of milder symptoms in some female carriers with other pathogenic variants (PMID: 31732614). In PMID: 31732614, marginally elevated protein excretion (150 mg/day) in a female carrier with the Thr780Ser variant considered pathogenic. Our proband also had VUS in ACTN4 (NM_004924.6:c.226G>A p.Glu76Lys, gene linked with familial idiopathic steroid-resistant nephrotic syndrome, AD inheritance) and VUS in TBX18 (NM_001080508.3:c.500G>A p.Arg167His, gene linked with congenital anomalies of kidney and urinary tract 2, AD inheritance). Moderate
872 M acute respiratory failure ND NM_001083619.3(GRIA2):c.1047_1048insGG (p.Gln350GlyfsTer12) het. P(10),PVS1,PM2 Neurodevelopmental disorder with language impairment and behavioral abnormalities, OMIM#138247 AD Death at 48 years, basic vocational education (3), unmarried, income per family member 300-500 zl. Pathogenic truncating variants found in ClinVar, both upstream (4-157317690-C-A) and downstream 4-157336489-A-AGAAGTCCAAACCAGGAGTGTTTTCCTTTCTT. The GRIA2 disease has a highly variable phenotype by OMIM. Respiratory dysfunction such as central sleep apnea may be a feature of the GRIA2 disease PMID: 40391499. Low
908 F non-allergic asthma CNV Ca NR-COD Removes CRKL, SERPIND1, SNAP29, PI4KA, THAP7, SLC7A4, LZTR1, AIFM3, P2RX6, LRRC74B genes but not TBX1. het. P score 1 (for CNV); slightly smaller, nested deletions classified as P (ClinVarID:59237) or LP (ClinVarID:4852046) 22q11.2 DiGeorge region deletion AD Corresponds to nested "central" deletion in DiGeorge syndrome region located between LCR22-C and LCR22-D (known as a CDdel, PMID: 39858619). Although it is not associated with the full DiGeorge syndrome phenotype, abnormal immune regulation and frequent infections have been reported (PMID: 22926078, PMID: 39858619) Moderate
909 M accident RF NM_000899.5(KITLG):c.715-2A>G het. P(10)PVS1,PM2_sup, PP5; ClinVar: P:2 U:2 Deafness, autosomal dominant 69, unilateral or asymmetric, OMIM#184745 AD Death at 47 years, BMI 29, cholesterol 310, triglycerides 1104. KITLG variant was described as pathogenic for age-related hearing loss (PMID: 33229591). Moderate
911 M ? Novel NM_002892.4(ARID4A):c.2171_2172insG (p.Asn724LysfsTer2) het. P(10)PVS1,PM2 Novel disease? AD Death at 34 years, basic vocational training (3), unmarried, unspecified income. Another truncating ARID4A variant NM_002892.4:c.2614G>T (p.Glu872Ter) classified in ClinVar as LP for Multiple myeloma (Variation ID: 800352) Low speculative
29914 M stroke MD NM_000459.5(TEK):c.672T>A (p.Cys224Ter) / NM_001009944.3(PKD1):c.10499+5G>A het. /het P(10)PVS1,PM2 / VUS (5) PM2, PP3_str. Venous malformations, multiple cutaneous and mucosal, OMIM#600221/ Polycystic kidney disease 1 OMIM#173900 AD /AD death at 49 years, RR 140/88, PKD1 disease spectrum includes intracranial aneurysm High
ACMG – variant in a gene listed in ACMG recommendations for secondary findings; Ca – cancer; CVD – cardiovascular disease; ND – neurodevelopmental disorder; MD – Mendelian disorder (other than ND); RF – risk factor; NR-COD – not related to cause of death; comp. het – compound heterozygosity; BMI – body mass index
Table 2. Persons with variants reportable according to the ACMG recommendations for secondary findings11.
Table 2. Persons with variants reportable according to the ACMG recommendations for secondary findings11.
ACMG gene list category Reference (N=1000) WOBASZ (N=127)
n % n %
Cardiovascular 31 3.1 6 4.7
Cancer 15 1.5 5 3.9*
Other 21 2.1 2 1.6
All 66# 6.6 13 10.2
# One subject had two variants; *p = 0.065, OR = 2.7 (Fisher’s exact test)
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.