Approaches of genetic signal detection in polygenic, multifactorial disorders
Török Dóra
Gyógyszertudományok és Egészségügyi Technológiák Tagozat
Dr. Zelkó Romána
SE Belgyógyászati és Onkológiai Klinika tanterme
2026-03-10 10:00:00
Experimental and Clinical Pharmacology
Dr. Szökő Éva
Dr. Juhász Gabriella és Dr. Petschner Péter
Dr. Szabó-Vereczkei Andrea
Dr. Kéri Szabolcs
Dr. Buzás Edit
Dr. Fóthi Ábel
Dr. Pinczés Dóra
The work presents novel strategies to improve genetic signal detection in polygenic disorders by combining refined phenotype definitions with biologically grounded, pathway-level analyses. Using migraine and depression phenotypes, it highlights how hypothesis-driven insights improve discovery and interpretability in genetics.
In migraine, focusing on individuals without comorbidities at disease onset, those whose first diagnosis was migraine, increased SNP-based heritability to 19.37%, compared to the previously reported 14.6%. This refined group showed stronger genetic signals, replicated known migraine loci (PRDM16, FHL5, ASTN2, STAT6/LRP1, SLC24A3), and identified suggestive associations in CALCB, a key CGRP coding gene.
Integrating findings of transcriptomic study in migraine, focusing on the vitamin A pathway, provided additional biological context. Although most differentially expressed genes showed no significant association, LRP1 emerged as a key gene: eleven SNPs were significantly associated with migraine, and seven replicated in an independent cohort, supporting its involvement in pathophysiology.
The pathway-based approach was then extended to depression. Based on rodent findings, NAD+/SIRT1 pathway polygenic risk scores were calculated and tested in interaction with early life stress. In males, NAD+/SIRT1 genetic risk in interaction with early life stress explained variance from depressive symptoms at 0.5037% with p-value of 0.0002. Body fat percentage did not mediate this effect. Resting-state fMRI revealed that these individuals also showed altered connectivity between the nucleus accumbens and prefrontal cortex regions (females, beta = -0.3850, p-value = 0.0010, males, beta = 0.3859, p-value = 0.0145), involved in reward and anhedonia. Notably, the increased connectivity observed in males aligns with patterns previously reported in melancholic depression.
Together, these findings show that precise phenotype selection and pathway-focused genetic analyses can improve signal detection and biological relevance. This work supports a shift from broad, noisy samples toward targeted, replicable frameworks in genetics.
