Genetic Predisposition To Disease Research Articles

Alzheimer's disease genetic pathways impact cerebrospinal fluid biomarkers and imaging endophenotypes in non-demented individuals.

Unraveling how Alzheimer's disease (AD) genetic risk is related to neuropathological heterogeneity, and whether this occurs through specific biological pathways, is a key step toward precision medicine. We computed pathway-specific genetic risk scores (GRSs) in non-demented individuals and investigated how AD risk variants predict cerebrospinal fluid (CSF) and imaging biomarkers reflecting AD pathology, cardiovascular, white matter integrity, and brain connectivity. CSF amyloidbeta and phosphorylated tau were related to most GRSs. Inflammatory pathways were associated with cerebrovascular disease, whereas quantitative measures of white matter lesion and microstructure integrity were predicted by clearance and migration pathways. Functional connectivity alterations were related to genetic variants involved in signal transduction and synaptic communication. This study reveals distinct genetic risk profiles in association with specific pathophysiological aspects in predementia stages of AD, unraveling the biological substrates of the heterogeneity of AD-associated endophenotypes and promoting a step forward in disease understanding and development of personalized therapies. Polygenic risk for Alzheimer's disease encompasses six biological pathways that can be quantified with pathway-specific genetic risk scores, and differentially relate to cerebrospinal fluid and imaging biomarkers. Inflammatory pathways are mostly related to cerebrovascular burden. White matter health is associated with pathways of clearance and membrane integrity, whereas functional connectivity measures are related to signal transduction and synaptic communication pathways.

Fluid Biomarkers in Individuals at Risk for Genetic Prion Disease up to Disease Conversion.

To longitudinally characterize disease-relevant CSF and plasma biomarkers in individuals at risk for genetic prion disease up to disease conversion. This single-center longitudinal cohort study has followed known carriers of PRNP pathogenic variants at risk for prion disease, individuals with a close relative who died of genetic prion disease but who have not undergone predictive genetic testing, and controls. All participants were asymptomatic at first visit and returned roughly annually. We determined PRNP genotypes, measured NfL and GFAP in plasma, and RT-QuIC, total PrP, NfL, T-tau, and beta-synuclein in CSF. Among 41 carriers and 21 controls enrolled, 28 (68%) and 15 (71%) were female, and mean ages were 47.5 and 46.1. At baseline, all individuals were asymptomatic. We observed RT-QuIC seeding activity in the CSF of 3 asymptomatic E200K carriers who subsequently converted to symptomatic and died of prion disease. 1 P102L carrier remained RT-QuIC negative through symptom conversion. No other individuals developed symptoms. The prodromal window from detection of RT-QuIC positivity to disease onset was 1 year long in an E200K individual homozygous (V/V) at PRNP codon 129 and 2.5 and 3.1 years in 2 codon 129 heterozygotes (M/V). Changes in neurodegenerative and neuroinflammatory markers were variably observed prior to onset, with increases observed for plasma NfL in 4/4 converters, and plasma GFAP, CSF NfL, CSF T-tau, and CSF beta-synuclein each in 2/4 converters, although values relative to age and fold changes relative to individual baseline were not remarkable for any of these markers. CSF PrP was longitudinally stable with mean coefficient of variation 9.0% across all individuals over up to 6 years, including data from converting individuals at RT-QuIC-positive timepoints. CSF prion seeding activity may represent the earliest detectable prodromal sign in E200K carriers. Neuronal damage and neuroinflammation markers show limited sensitivity in the prodromal phase. CSF PrP levels remain stable even in the presence of RT-QuIC seeding activity. ClinicalTrials.gov NCT05124392 posted 2017-12-01, updated 2023-01-27.

Development and assessment of a knowledge, attitude, and practice (KAP) questionnaire for genetic counselees with preimplantation genetic testing (PGT) indications

BackgroundPreimplantation genetic testing (PGT) can reduce the risk of familial genetic diseases, chromosome abnormalities, and recurrent abortions. It is unclear whether genetic counselees with PGT indications understand and accept the implications of PGT. A well-developed and validated tool is needed to evaluate the knowledge, attitude, and practice (KAP) levels of genetic counselees with PGT indications. The purpose of this study was to develop and validate a PGT KAP questionnaire (PGT-KAP-Q) for genetic counselees with PGT indications. MethodsFirst, we established an item pool based on a literature review and qualitative interviews. Second, we developed the PGT-KAP-Q using the Delphi method. Third, we evaluated the quality of the questionnaire using item analysis and psychometric evaluation. The item analysis included extreme value comparison, application of the correlation and Cronbach's alpha (α) coefficient methods, and factor analysis. We also evaluated the content and structural validity of the questionnaire, as well as the internal consistency, test–retest reliability, and split-half reliability. FindingsAfter the literature review and interviews, and based on three rounds of expert consultations, we formed a 43-item questionnaire. In the validity analysis, the item's content validity index (I-CVI) and the average scale level CVI (S-CVI/Ave) values (>0.78 and >0.95, respectively) confirmed the questionnaire's content validity. Exploratory factor analysis showed that all 43 items had strong factor loadings (>0.4), and the three factors of the PGT-KAP-Q explained 51.97 % of the total variance. The Cronbach's α coefficient for the questionnaire was 0.95 (p < 0.05), the split-half reliability was 0.76 (p < 0.05) and the test–retest reliability coefficient was 0.78 (p < 0.05). InterpretationThe 43-item PGT-KAP-Q for genetic counselees with PGT indications is reliable and valid. It contains a moderate number of items, is easy for patients to understand and accept, and can be used for clinical research and applications.

Unveiling novel genetic variants in 370 challenging medically relevant genes using the long read sequencing data of 41 samples from 19 global populations.

A large number of challenging medically relevant genes (CMRGs) are situated in complex or highly repetitive regions of the human genome, hindering comprehensive characterization of genetic variants using next-generation sequencing technologies. In this study, we employed long-read sequencing technology, extensively utilized in studying complex genomic regions, to characterize genetic alterations, including short variants (single nucleotide variants and short insertions and deletions) and copy number variations, in 370 CMRGs across 41 individuals from 19 global populations. Our analysis revealed high levels of genetic variants in CMRGs, with 68.73% exhibiting copy number variations and 65.20% containing short variants that may disrupt protein function across individuals. Such variants can influence pharmacogenomics, genetic disease susceptibility, and other clinical outcomes. We observed significant differences in CMRG variation across populations, with individuals of African ancestry harboring the highest number of copy number variants and short variants compared to samples from other continents. Notably, 15.79% to 33.96% of short variants were exclusively detectable through long-read sequencing. While the T2T-CHM13 reference genome significantly improved the assembly of CMRG regions, thereby facilitating variant detection in these regions, some regions still lacked resolution. Our results provide an important reference for future clinical and pharmacogenetic studies, highlighting the need for a comprehensive representation of global genetic diversity in the reference genome and improved variant calling techniques to fully resolve medically relevant genes.

Towards cascading genetic risk in Alzheimer's disease.

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: Amyloid (A), Tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, where each of the biomarkers can be either positive (+) or negative (-). Over the past decades genome wide association studies have implicated about 90 different loci involved with the development of late onset Alzheimer's disease. Here we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we employed Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex, and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed significant effect (HR=2.88; 95% CI: 1.70-4.89; P<0.001), while polygenic risk did not (HR=1.09; 95% CI: 0.84-1.42; P=0.53). Conversely, for the transition from A+T- to A+T+, the APOE-e4 burden contribution was reduced (HR=1.62 95% CI: 1.05-2.51; P=0.031), while the polygenic risk showed an increased contribution (HR=1.73; 95% CI:1.27-2.36; P<0.001). The marginal APOE effect was driven by e4 homozygotes (HR=2.58; 95% CI: 1.05-6.35; P=0.039) as opposed to e4 heterozygotes (HR=1.74; 95% CI: 0.87-3.49; P=0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of transition between ATN stages, a better understanding of the molecular processes leading to Alzheimer's disease as well as opening therapeutic windows for targeted interventions.

Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders.

Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine. We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort. Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable. Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.

Prenatal Diagnosis of Cystic Fibrosis by Celocentesis.

Celocentesis is a new sampling tool for prenatal diagnosis available from 7 weeks in case of couples at risk for genetic diseases. In this study, we reported the feasibility of earlier prenatal diagnosis by celocentesis in four cases of cystic fibrosis and one case of cystic fibrosis and β-thalassemia co-inherited in the same fetus. Celomic fluids were aspired from the celomic cavity between 8+2 and 9+3 weeks of gestation and fetal cells were picked up by micromanipulator. Maternal DNA contamination was tested and target regions of fetal DNA containing parental pathogenetic variants of CFTR and HBB genes were amplified and sequenced. Four of the five fetuses resulted as being affected by cystic fibrosis and, in all cases, the women decided to interrupt the pregnancy. In the other case, the fetus presented a healthy carrier of cystic fibrosis. The results were confirmed in three cases on placental tissue. In one case, no abortive tissue was obtained. In the last case, the woman refused the prenatal diagnosis to confirm the celocentesis data; the pregnancy is ongoing without complications. This procedure provides prenatal diagnosis of monogenic diseases at least four weeks earlier than traditional procedures, reducing the anxiety of patients and providing the option for medical termination of the affected fetus at 8-10 weeks of gestation, which is less traumatic and safer than surgical termination in the second trimester.

Sleep patterns, genetic susceptibility, and digestive diseases: A large-scale longitudinal cohort study.

Sleep problems are prevalent. However, the impact of sleep patterns on digestive diseases remains uncertain. Moreover, the interaction between sleep patterns and genetic predisposition with digestive diseases has not been comprehensively explored. 410,586 participants from UK Biobank with complete sleep information were included in the analysis. Sleep patterns were measured by sleep scores as the primary exposure, based on five healthy sleep behaviors. Individual sleep behaviors were secondary exposures. Genetic risk of the digestive diseases was characterized by polygenic risk score. Primary outcome was incidence of 16 digestive diseases. Healthy sleep scores showed dose-response associations with reduced risks of digestive diseases. Compared to participants scoring 0-1, those scoring 5 showed a 28% reduced risk of any digestive disease, including a 50% decrease in irritable bowel syndrome, 37% in non-alcoholic fatty liver disease, 35% in peptic ulcer, 34% in dyspepsia, 32% in gastroesophageal reflux disease, 28% in constipation, 25% in diverticulosis, 24% in severe liver disease, and 18% in gallbladder disease, whereas no correlation was observed with inflammatory bowel disease and pancreatic disease. Participants with poor sleep and high genetic risk exhibited approximately a 60% increase in the risk of digestive diseases. A healthy sleep pattern is linked to lower digestive disease risk in participants of all genetic risk levels. In this large population-based cohort, a healthy sleep pattern was associated with reduced risk of digestive diseases, regardless of the genetic susceptibility. Our findings underscore the potential impact of healthy sleep traits in mitigating the risk of digestive diseases.

Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer

Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n= 3,323) and non-oral LP (n= 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.

Variants in the MS4A cluster interact with soluble TREM2 expression on biomarkers of neuropathology

Recent evidence suggests that Alzheimer’s disease (AD) genetic risk variants (rs1582763 and rs6591561) of the MS4A locus are genome-wide significant regulators of soluble TREM2 levels such that the minor allele of the protective variant (rs1582763) is associated with higher sTREM2 and lower AD risk while the minor allele of (rs6591561) relates to lower sTREM2 and higher AD risk. Our group previously found that higher sTREM2 relates to higher Aβ40, worse blood–brain barrier (BBB) integrity (measured with the CSF/plasma albumin ratio), and higher CSF tau, suggesting strong associations with amyloid abundance and both BBB and neurodegeneration complicate interpretation. We expand on this work by leveraging these common variants as genetic tools to tune the interpretation of high CSF sTREM2, and by exploring the potential modifying role of these variants on the well-established associations between CSF sTREM2 as well as TREM2 transcript levels in the brain with AD neuropathology. Biomarker analyses leveraged data from the Vanderbilt Memory & Aging Project (n = 127, age = 72 ± 6.43) and were replicated in the Alzheimer’s Disease Neuroimaging Initiative (n = 399, age = 73 ± 7.39). Autopsy analyses were performed leveraging data from the Religious Orders Study and Rush Memory and Aging Project (n = 577, age = 89 ± 6.46). We found that the protective variant rs1582763 attenuated the association between CSF sTREM2 and Aβ40 (β = -0.44, p-value = 0.017) and replicated this interaction in ADNI (β = -0.27, p = 0.017). We did not observe this same interaction effect between TREM2 mRNA levels and Aβ peptides in brain (Aβ total β = -0.14, p = 0.629; Aβ1-38, β = 0.11, p = 0.200). In contrast to the effects on Aβ, the minor allele of this same variant seemed to enhance the association with blood–brain barrier dysfunction (β = 7.0e-4, p = 0.009), suggesting that elevated sTREM2 may carry a much different interpretation in carriers vs. non-carriers of this allele. When evaluating the risk variant (rs6591561) across datasets, we did not observe a statistically significant interaction against any outcome in VMAP and observed opposing directions of associations in ADNI and ROS/MAP on Aβ levels. Together, our results suggest that the protective effect of rs1582763 may act by decoupling the associations between sTREM2 and amyloid abundance, providing important mechanistic insight into sTREM2 changes and highlighting the need to incorporate genetic context into the analysis of sTREM2 levels, particularly if leveraged as a clinical biomarker of disease in the future.

A Novel Macrophage Subpopulation Conveys Increased Genetic Risk of Coronary Artery Disease.

Coronary artery disease (CAD), the leading cause of death worldwide, is influenced by both environmental and genetic factors. Although over 250 genetic risk loci have been identified through genome-wide association studies, the specific causal variants and their regulatory mechanisms are still largely unknown, particularly in disease-relevant cell types such as macrophages. We utilized single-cell RNA-seq and single-cell multiomics approaches in primary human monocyte-derived macrophages to explore the transcriptional regulatory network involved in a critical pathogenic event of coronary atherosclerosis-the formation of lipid-laden foam cells. The relative genetic contribution to CAD was assessed by partitioning disease heritability across different macrophage subpopulations. Meta-analysis of single-cell RNA-seq data sets from 38 human atherosclerotic samples was conducted to provide high-resolution cross-referencing to macrophage subpopulations in vivo. We identified 18 782 cis-regulatory elements by jointly profiling the gene expression and chromatin accessibility of >5000 macrophages. Integration with CAD genome-wide association study data prioritized 121 CAD-related genetic variants and 56 candidate causal genes. We showed that CAD heritability was not uniformly distributed and was particularly enriched in the gene programs of a novel CD52-hi lipid-handling macrophage subpopulation. These CD52-hi macrophages displayed significantly less lipoprotein accumulation and were also found in human atherosclerotic plaques. We investigated the cis-regulatory effect of a risk variant rs10488763 on FDX1, implicating the recruitment of AP-1 and C/EBP-β in the causal mechanisms at this locus. Our results provide genetic evidence of the divergent roles of macrophage subsets in atherogenesis and highlight lipid-handling macrophages as a key subpopulation through which genetic variants operate to influence disease. These findings provide an unbiased framework for functional fine-mapping of genome-wide association study results using single-cell multiomics and offer new insights into the genotype-environment interactions underlying atherosclerotic disease.

Prevalence of kidney health genetic variants in adults with sickle cell nephropathy.

The pathophysiology and genetic risk for sickle cell disease (SCD)-related chronic kidney disease (CKD) are not well understood. In 70 adults with SCD-related CKD and without APOL1 inherited in a high-risk pattern, 24 (34%) had pathogenic variants in candidate genes using KidneySeq™. A moderate impact INF2 variant was observed in 20 (29%) patients and those with 3 versus 0-2 pathogenic or moderate impact glomerular genetic variants had higher albuminuria and lower estimated glomerular filtration rate (adjusted p ≤ 0.015). Using a panel of preselected genes implicated in kidney health, we observed several variants in people with sickle cell nephropathy.

All of Us participant perspectives on the return of value in research

PurposeTo understand participant preferences for receiving specific types of research information, whether information preferences vary across sociodemographic groups, and the types of health providers participants could access to understand returned information. MethodsAll of Us Research Program participants completed a value of returning research information survey. Stratified sampling was implemented to enhance participant diversity and avoid noncoverage. We used weighted multivariable logistic regression to evaluate associations between the most valuable information types, access to providers, and sociodemographic variables. ResultsParticipants (N = 20,405) were diverse in their race/ethnicity (eg, 52% were White, 18% were Hispanic/Latino or Spanish, 3% were Asian, and 20% were Black or African American). Most participants (78.6%) valued information about their risk of serious genetic diseases with available treatment. Primary care physicians, specialists, and genetic counselors were the top providers that participants could access for help understanding returned information. Information preferences and provider access varied across sociodemographic groups. For example, as income levels increased, the odds of placing value on genetic results indicating risk of serious disease with available treatment increased when compared with the lowest income levels (P value < .001). ConclusionAlthough genetic information was most valuable to participants, preferences about specific information types varied across sociodemographic groups.

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study.

The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non-shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

Interactions between physical exercise, associative memory, and genetic risk for Alzheimer's disease.

The ε4 allele of the APOE gene heightens the risk of late onset Alzheimer's disease. ε4 carriers, may exhibit cognitive and neural changes early on. Given the known memory-enhancing effects of physical exercise, particularly through hippocampal plasticity via endocannabinoid signaling, here we aimed to test whether a single session of physical exercise may benefit memory and underlying neurophysiological processes in young ε3 carriers (ε3/ε4 heterozygotes, risk group) compared with a matched control group (homozygotes for ε3). Participants underwent fMRI while learning picture sequences, followed by cycling or rest before a memory test. Blood samples measured endocannabinoid levels. At the behavioral level, the risk group exhibited poorer associative memory performance, regardless of the exercising condition. At the brain level, the risk group showed increased medial temporal lobe activity during memory retrieval irrespective of exercise (suggesting neural compensatory effects even at baseline), whereas, in the control group, such increase was only detectable after physical exercise. Critically, an exercise-related endocannabinoid increase correlated with task-related hippocampal activation in the control group only. In conclusion, healthy young individuals carrying the ε4 allele may present suboptimal associative memory performance (when compared with homozygote ε3 carriers), together with reduced plasticity (and functional over-compensation) within medial temporal structures.

Abstract PO2-08-03: Developing a polygenic risk score for precision prevention of estrogen receptor-positive (ER+)/HER2- breast cancer in Brazilian women

Abstract Polygenic risk scores (PRS) quantify the genetic risk of diseases based on risk alleles in genomic loci identified in genome-wide association studies (GWAS). As individuals of European ancestry are overrepresented in GWAS, PRS performance may vary in individuals of different ancestries. Brazil is the largest and most populated country in Latin America, with around 43% of admixed individuals, and data on breast cancer PRS performance for this population is lacking. We aimed to evaluate the performance of a breast cancer PRS with 313 SNPs generated with Europeans in Brazilian population. In this case-control study, we expect to include 1000 women age &amp;gt;= 18 years old with current or previous diagnosis of ER+/HER2- breast cancer. Germline DNA samples are genotyped with Illumina Infinium Global Screening Array-24 v3.0 chip. Controls are healthy woman previously genotyped with Global Screening Array-24 v1.0 chip. We selected the 313 SNPs PRS for ER+/HER2- breast cancer from PGS Catalog for evaluation. Quality control, imputation, PRS calculation and statistical analysis were performed in PLINK v2.0, Michigan server, PGS Catalog and R, respectively. We present the preliminary results for 1347 women (504 cases and 843 controls) included until March of 2023. After quality control and imputation, we calculated PRS for 1212 subjects (475 cases and 737 controls). Out of 313 SNPs, 211 were validated in our samples. For ER+/HER2- breast cancer, the odds ratio per SD of the 211-variant PRS (PRS211) was 1.363 (95% confidence interval [CI]: 1.211 to 1.537). Compared with women with average risk (40th-60th PRS percentile), women in the top 10% of PRS211 had a 1.623-fold increased risk (95% CI: 1.047 to 2.522). The area under the receiver operating characteristic curve of 0.581. Our preliminary results indicate that a PRS derived from European-ancestry population correlates with ER+/HER2- breast cancer in admixed Brazilian population, although with attenuated performance. Further work is needed to better characterize PRS risk stratification in admixed populations. Citation Format: Marina Candido Visontai Cormedi, Álison Luís Eburnêo Pereira, Fernanda Borchers Coeli-Lacchini, Sabrina Baroni, Lívia Mara Torres Bueno, Evelyn Ayumi Onga, Victor Girelli Piloto De Oliveira, Fabiana De Oliveira Buono, Aline Fares, Tatiana Strava Correa, Iasmin Alves Chirichela, Fernanda Peria, Romulado Barroso-Sousa, Rodrigo Santa Cruz Guindalini, Taisa Manuela Bonfim Machado Lopes, Rosimeire Aparecida Roela, Maria Aparecida Azevedo Koike Folgueira, Daniel Guimarães Tiezzi, Leandro Machado Colli, Liane Rapatoni. Developing a polygenic risk score for precision prevention of estrogen receptor-positive (ER+)/HER2- breast cancer in Brazilian women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-08-03.

In vivo validation of late-onset Alzheimer's disease genetic risk factors.

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics. A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

A State-of-the-art Review on Artificial Intelligence and Machine Learning Applications

Background: The integration of artificial intelligence and machine learning holds great promise for enhancing healthcare institutions and providing fresh perspectives on the origins and advancement of long-term illnesses. In the healthcare sector, artificial intelligence and machine learning are used to address supply and demand concerns, genomic applications, and new advancements in drug development, cancer, and heart disease. Objective: The article explores the ways that machine learning, AI, precision medicine, and genomics are changing healthcare. The essay also discusses how AI's examination of various patient data could enhance healthcare institutions, provide fresh insights into chronic conditions, and advance precision medicine. The potential uses of machine learning for genome analysis are also examined in the paper, particularly about genetic biomarker-based disease risk and symptom prediction. Discussion: The challenges posed by the phenotype-genotype relationship are examined, as well as the significance of comprehending disease pathways in order to create tailored treatments. Moreover, it offers a streamlined and modularized method that predicts how genotypes affect cell properties using machine-learning models, enabling the development of personalized drugs. The collective feedback highlights the rapid interdisciplinary growth of medical genomics following the completion of the Human Genome Project. It also emphasizes how important genomic data is for improving healthcare outcomes and facilitating personalized medicine. Conclusion: The study's conclusions point to a revolutionary shift in healthcare: the application of AI/ML to illness control. Even though these innovations have a lot of potential benefits, problems like algorithm interpretability and ethical issues need to be worked out before they can be successfully incorporated into routine medical practice. Using machine learning in medicine has enormous potential benefits for the biotech industry. Further research, ongoing regulatory frameworks, and collaboration between medical professionals and data analysts are necessary to fully utilize machine learning as well as artificial intelligence in disease management.

Alzheimer's disease genetic risk score and neuroimaging in the FINGER lifestyle trial.

We assessed a genetic risk score for Alzheimer's disease (AD-GRS) and apolipoprotein E (APOE4) in an exploratory neuroimaging substudy of the FINGER trial. 1260 at-risk older individuals without dementia were randomized to multidomain lifestyle intervention or health advice. N=126 participants underwent magnetic resonance imaging (MRI), and N=47 positron emission tomography (PET) scans (Pittsburgh Compund B [PiB], Fluorodeoxyglucose) at baseline; N=107 and N=38 had repeated 2-year scans. The APOE4 allele, but not AD-GRS, was associated with baseline lower hippocampus volume (β=-0.27, p=0.001), greater amyloid deposition (β=0.48, p=0.001), 2-year decline in hippocampus (β=-0.27, p=0.01), total gray matter volume (β=-0.25, p=0.01), and cortical thickness (β=-0.28, p=0.003). In analyses stratified by AD-GRS (below vs above median), the PiB composite score increased less in intervention versus control in the higher AD-GRS group (β=-0.60, p=0.03). AD-GRS and APOE4 may have different impacts on potential intervention effects on amyloid, that is, less accumulation in the higher-risk group (AD-GRS) versus lower-risk group (APOE). First study of neuroimaging and AD genetics in a multidomain lifestyle intervention. Possible intervention effect on brain amyloid deposition may rely on genetic risk. AD-GRS and APOE4 allele may have different impacts on amyloid during intervention.

Sleep and circadian biomarkers of postoperative delirium (SLEEP-POD): protocol for a prospective and observational cohort study

IntroductionSurgical patients over 70 experience postoperative delirium (POD) complications in up to 50% of procedures. Sleep/circadian disruption has emerged as a potential risk factor for POD in epidemiological studies. This...