# Decoding the impact of sex differences on Alzheimer's disease risk

> **NIH NIH R01** · BAYLOR COLLEGE OF MEDICINE · 2021 · $1,201,822

## Abstract

Decoding the Impact of Sex Differences on Alzheimer’s Disease Risk
The molecular basis and genetic architecture of Alzheimer’s Disease (AD) remain poorly defined. Solving these
problems is further complicated by the differences that exist between men and women with respect to the
prevalence, onset, progression and comorbidities of AD, suggesting that some contributing genetic variants are
sex-specific. So far, mixed-gender Genome-wide association studies (GWAS) have linked over 100 loci with AD.
These loci explain much of the population-attributable risk but just a fraction of heritability, and with no distinction
between men and women. It is unlikely that this heritability gap would improve just by splitting studies by sex,
however, since separate analyses on about half as many patients would be less powerful. Rather, in order to
design effective surveillance, screening, preventive, and stratification programs tailored to each sex, there is a
critical need for more sensitive and accurate methods, able to compute the link between genetic variants and
AD risk separately and specifically in men and women. To do so, we propose an integrative computational
approach that will be validated by experimental and translational studies of candidate genes. Rather than seek
individual variants, we focus instead on genes and their coding regions. In order to increase the power of our
studies, we developed an unbiased evolution-based continuous score for the functional impact of any coding
variant, from 0 (neutral) to 1 (complete loss of function). Using this scoring system adds to the usual analyses of
human variants a vast number of amino acid mutation experiments already performed by evolution over billions
of years, with each mutation being tied to a functional readout based on the context of its phylogenetic divergence.
With this score, we now propose to identify genes that carry significantly more impactful coding variants in AD
women, or AD men, compared to sex-matched controls. The gain in statistical power of this approach compared
to GWAS has been demonstrated in preliminary data. In Aim 1 we propose to discover sex-specific AD genes
on more than 1000 Alzheimer’s Disease Sequencing Project (ADSP) men and 1400 ADSP women; and in Aim
2 to discover sex-specific modifiers of APOE. Aim 3 will include validation of computationally-derived candidate
genes in human brain tissue and cerebrospinal fluid (CSF), and thorough experimental characterization in AD
animal-models (mouse and Drosophila). Together, this combination of novel, integrative computational
approaches and multi-model systems validation experiments will yield new biomarkers that improve sex-specific
risk stratification of AD status and reveal differences in disease mechanisms between women and men that
highlight potential therapeutic targets specific to each.

## Key facts

- **NIH application ID:** 10300802
- **Project number:** 1R01AG074009-01
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Ismael Al-Ramahi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,201,822
- **Award type:** 1
- **Project period:** 2021-09-15 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10300802

## Citation

> US National Institutes of Health, RePORTER application 10300802, Decoding the impact of sex differences on Alzheimer's disease risk (1R01AG074009-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10300802. Licensed CC0.

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