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PubMed2026

Trio-based GWAS reveals loci associated with different forms of isolated cleft lip.

Orofacial clefts (OFCs) are the most common craniofacial birth defect and comprise a diverse group of traits with complex and heterogeneous etiologies. Genetic studies of OFCs typically approach this diversity by stratifying cases into broad diagnostic classes, including cleft lip (CL), cleft palate (CP), and cleft lip with palate (CLP). Although this strategy has yielded important insights into OFC risk, it ignores the phenotypic heterogeneity within each subtype. CL exhibits marked phenotypic variability, involving differences in alveolar involvement, laterality, and sidedness that may reflect distinct etiologies. Given this phenotypic diversity within CL, we assembled a multi-ancestry cohort of 837 nonsyndromic CL case-parent trios with whole-genome sequencing and detailed phenotyping. We performed genome-wide association scans (GWAS) via transmission disequilibrium tests for CL overall and for 14 CL subtypes defined by involvement of the alveolus (with and without), laterality (uni- and bilateral), and sidedness (left and right). We identified four genome-wide significant loci. Two loci, IRF6 and 8q24.21, were both detected in the overall CL GWAS. PLCB1/PLCB4 and MAFB were detected in GWASs of alveolar cleft involvement and CL left sidedness, respectively. These subtype-specific associations were followed by case-only comparisons that reflect the presence or absence of alveolus cleft or left-sided bias of CL to confirm the specificity of the association signal to the particular subtype. Our results provide evidence of within-class CL subtype-specific genetic links for loci previously discussed in the context of primary OFC classes and demonstrate the value of granular OFC subtype characterization to capture trait-specific associations.

Alveolus Cleft↗
PubMed2026

Frequency and clinical features of germline pathogenic variants in sarcoma: a case-control study.

BACKGROUND: Germline multigene panel testing is not yet integrated into standard care for patients with sarcoma. This study aimed to assess the frequency and distribution of germline pathogenic variants in patients with sarcoma compared with cancer-free controls and identify differences between patients with and without germline pathogenic variants. METHODS: This retrospective cohort included 488 sarcoma patients and 2440 cancer-free controls matched 1:5 by age, sex, and ethnicity. Multigene panel testing was performed between 2016 and 2024 at a single germline testing laboratory. The frequency of germline pathogenic variants in selected genes was compared using Fisher exact test with odds ratios (ORs) and 95% confidence intervals. Additionally, within the case-only cohort, clinical characteristics were evaluated to assess associations with the presence of germline pathogenic variants in any gene. RESULTS: Among 488 patients with sarcoma, 67.8% (n&#x2009;=&#x2009;331) were female, with a median age at sarcoma diagnosis of 47&#x2009;years (range = 0.5-87.5 years). Cases had a higher frequency of germline pathogenic variants compared with controls (26.2% vs 10.5%; OR = 3.05, P&#x2009;<&#x2009;.001). We observed a higher frequency of germline pathogenic variants in TP53, BRCA2, CHEK2, NF1, SDHA, BRIP1, POT1, RB1, and CDH1 among patients with sarcoma compared with controls. Age at sarcoma diagnosis did not differ between groups. CONCLUSIONS: This study confirms the high detection rate of germline pathogenic variants in patients with sarcoma and describes several associated genes. These findings indicate that age at sarcoma diagnosis may not reliably predict germline pathogenic variants. Expanding germline testing for patients with sarcoma would enhance personalized treatment strategies and familial risk assessment.

Humans↗
PubMed2025

A comprehensive evaluation of candidate genetic polymorphisms in a large histologically characterized MASLD cohort using a novel framework.

BACKGROUND: There is a substantial heritable component to metabolic dysfunction-associated steatotic liver disease (MASLD), and several genetic variants that promote MASLD development or associate with its severity have been reported. These associations vary in terms of their effect size and degree of replication. METHODS: We developed a framework to classify previously identified MASLD genetic polymorphisms into 4 tiers based on effect size and extent of replication in the literature. We tested the association between "tier 1" single-nucleotide polymorphisms (OR &#x2265;1.5, replicated in >2 independent studies) and biopsy measures of MASLD severity in a large, well-characterized histologic cohort of MASLD patients (n=3094). RESULTS: Across 19 "tier 1" variants reflecting 11 genetic loci, only those in the PNPLA3-SAMM50-PARVB locus showed significant associations with biopsy-proven fibrosis severity and NAFLD activity score; the highest risk was for the rs738409 p.I148M variant in PNPLA3. A genetic risk score based on "tier 1" variants, as well as a previously developed genetic risk score based on variants in PNPLA3, TM6SF2, and HSD17B13, were both associated with fibrosis and NAFLD activity score, but these results were driven entirely by PNPLA3 rs738409. CONCLUSIONS: Our study provides a framework to prioritize evaluation of genetic polymorphisms for future replication efforts and demonstrates that in a large case-only cohort, histologic severity of MASLD is only robustly associated with the presence of variation in PNPLA3 among known candidate genes. These findings may have implications for patient risk stratification based on the presence of PNPLA3 rs738409.

Humans↗
PubMed2025

Patient stratification by genetic risk in Alzheimer's disease is only effective in the presence of phenotypic heterogeneity.

Case-only designs in longitudinal cohorts are a valuable resource for identifying disease-relevant genes, pathways, and novel targets influencing disease progression. This is particularly relevant in Alzheimer's disease (AD), where longitudinal cohorts measure disease "progression," defined by rate of cognitive decline. Few of the identified drug targets for AD have been clinically tractable, and phenotypic heterogeneity is an obstacle to both clinical research and basic science. In four cohorts (n = 7241), we performed genome-wide association studies (GWAS) and Mendelian randomization (MR) to discover novel targets associated with progression and assess causal relationships. We tested opportunities for patient stratification by deriving polygenic risk scores (PRS) for AD risk and severity and tested the value of these scores in predicting progression. Genome-wide association studies identified no loci associated with progression at genome-wide significance (&#x3b1; = 5&#xd7;10-8); MR analyses provided no significant evidence of an association between cognitive decline in AD patients and protein levels in brain, cerebrospinal fluid (CSF), and plasma. Polygenic risk scores for AD risk did not reliably stratify fast from slow progressors; however, a deeper investigation found that APOE &#x3b5;4 status predicts amyloid-&#x3b2; and tau positive versus negative patients (odds ratio for an additional APOE &#x3b5;4 allele = 5.78 [95% confidence interval: 3.76-8.89], P<0.001) when restricting to a subset of patients with available CSF biomarker data. These results provided no evidence for large-effect, common-variant loci involved in the rate of memory decline, suggesting that patient stratification based on common genetic risk factors for progression may have limited utility. Where clinically relevant biomarkers suggest diagnostic heterogeneity, there is evidence that a priori identified genetic risk factors may have value in patient stratification. Mendelian randomization was less tractable due to the lack of large-effect loci, and future analyses with increased samples sizes are needed to replicate and validate our results.

Alzheimer Disease↗
PubMed2026

Methods for&#xa0;modeling gene-environment interplay using polygenic risk scores.

Polygenic risk scores (PRS) are increasingly recognized as pivotal tools for quantifying disease risk through the aggregation of multiple genetic variants. As sample sizes in genome-wide association studies (GWAS) continue to expand and PRS become more powerful, they are set to play a key role in translational research and personalized medicine. Understanding the interplay of PRS with environmental factors is critical for interpreting and applying PRS in diverse contexts. This interplay manifests in two forms: PRS-by-environment interaction (PRS&#xa0;&#xd7;&#xa0;E) and gene-environment correlation (rGE). However, despite the growing application and importance of PRS, there are limited guidelines for performing PRS&#xa0;&#xd7;&#xa0;E interaction analyses while controlling for rGE, which can lead to inconsistencies across studies and misinterpretation of results. Here we provide a review of different methods for performing PRSxE interaction in various epidemiological study designs, propose recommendations for best-practice, and discuss future challenges.

Gene-Environment Interaction↗