How understudied populations have contributed to our understanding of Alzheimer's disease genetics

Aging, Race, and Health Disparities: Recommendations From the Research Centers Collaborative Network

Racial disparities in adverse health outcomes with aging have been well described. Yet, much of the research focuses on racial comparisons, with relatively less attention to the identification of underlying mechanisms. To address these gaps, the Research Centers Collaborative Network held a workshop on aging, race, and health disparities to identify research priorities and inform the investigation, implementation, and dissemination of strategies to mitigate disparities in healthy aging. This article provides a summary of the key recommendations and highlights the need for research that builds a strong evidence base with both clinical and policy implications. Successful execution of these recommendations will require a concerted effort to increase participation of underrepresented groups in research through community engagement and partnerships. In addition, resources to support and promote the training and development of health disparities researchers will be critical in making health equity a shared responsibility for all major stakeholders.

Discrimination of Multiple Homologous Sequences Based on DNA Logic Gate and Elemental Labeling Technology

The simultaneous discrimination of multiple homologous sequences faces challenges due to the high similarity of sequences and the complexity of the discrimination system in most reported works. Herein, a simple and ingenious analysis method was developed to identify eight miRNAs of the let-7 family by combining logic gates and entropy-driven catalytic (EDC)-based lanthanide labeling inductively coupled plasma mass spectrometry (ICP-MS) technology. Specifically, eight miRNAs were first divided into four types according to the difference of bases in the domains 2 and 3 on sequences. To identify the type of targets, a DNA logic gate was constructed with two strand displacement reactions on magnetic beads that could be initiated by different types of targets. Based on the difference of the output signals after two strand displacement reactions, the type of targets was distinguished preliminarily. Then, the discrimination of a specific target was achieved with EDC-based lanthanide labeling ICP-MS detection. By labeling the different magnetic probes with different elemental tags, a specific element signal released from magnetic beads after EDC could be detected by ICP-MS, and therefore, simultaneous detection of homologous sequences was completed. This work provided a novel and simple method for highly specific identification of homologous sequences with the assistance of a logic gate and can promote further development of elemental labeling ICP-MS in the field of multiple analysis.

Whole-Exome Sequencing Study of Consanguineous Parkinson's Disease Families and Related Phenotypes: Report of Twelve Novel Variants

Parkinson's disease (PD) is a common progressive neurodegenerative disorder with motor and nonmotor symptoms. Recent studies demonstrate various susceptibility loci and candidate genes for familial forms of the disease. However, the genetic basis of the familial form of early-onset PD (EOPD) is not widely studied in the Iranian population. Therefore, the present study aimed to investigate the possible causative genetic variants responsible for developing EOPD among Iranian patients. Iranian patients with a clinical diagnosis of Parkinson's disease were evaluated, and 12 consanguineous families with at least two affected individuals with early-onset PD (EOPD) were chosen to enroll in the present study. An expert neurologist group examined these families. Whole-exome sequencing (WES) was performed on PD patients, and the possible causative genetic variants related to the development of PD were reported. Exome sequencing (WES) was performed on every PD patient and revealed that patients had novel genetic variants in PRKN, PARK7, and PINK1 genes. All the genetic variants were in homozygous status and none of these variants were previously reported in the literature. Moreover, these genetic variants were "pathogenic" based on bioinformatic studies and according to the American College of Medical Genetics (ACMG). The present research revealed some novel variants for EOPD among the Iranian population. Further functional studies are warranted to confirm the pathogenicity of these novel variants and establish their clinical application for the early diagnosis of EOPD.

Transfer learning for genotype-phenotype prediction using deep learning models

BACKGROUND

For some understudied populations, genotype data is minimal for genotype-phenotype prediction. However, we can use the data of some other large populations to learn about the disease-causing SNPs and use that knowledge for the genotype-phenotype prediction of small populations. This manuscript illustrated that transfer learning is applicable for genotype data and genotype-phenotype prediction.

RESULTS

Using HAPGEN2 and PhenotypeSimulator, we generated eight phenotypes for 500 cases/500 controls (CEU, large population) and 100 cases/100 controls (YRI, small populations). We considered 5 (4 phenotypes) and 10 (4 phenotypes) different risk SNPs for each phenotype to evaluate the proposed method. The improved accuracy with transfer learning for eight different phenotypes was between 2 and 14.2 percent. The two-tailed p-value between the classification accuracies for all phenotypes without transfer learning and with transfer learning was 0.0306 for five risk SNPs phenotypes and 0.0478 for ten risk SNPs phenotypes.

CONCLUSION

The proposed pipeline is used to transfer knowledge for the case/control classification of the small population. In addition, we argue that this method can also be used in the realm of endangered species and personalized medicine. If the large population data is extensive compared to small population data, expect transfer learning results to improve significantly. We show that Transfer learning is capable to create powerful models for genotype-phenotype predictions in large, well-studied populations and fine-tune these models to populations were data is sparse.

Validation of the Norma Latina Neuropsychological Assessment Battery in Patients with Alzheimer's Disease in Mexico

To our knowledge, this is the first study reported in the literature that has validated the Norma Latina Battery in a population of people with Alzheimer's disease (AD) in Mexico. The objective of the study was to determine the discriminant validity of the Norma Latina Battery in a group of Mexican individuals with AD and a group of heathy controls (HC). The Norma Latina Battery was administered to 234 Mexican participants (117 HC and 117 individuals with AD). Results show that: (1) the Norma Latina Battery has high discriminative capacity between groups in all domains; (2) participants with AD presented worse scores in each of the cognitive domains compared to the HC and a greater number of low scores in each of the established thresholds or cut-off points; and finally, (3) the Norma Latina Battery had optimal sensitivity and specificity, especially when a set was observed ≥5 scores below the 10th percentile or ≥4 scores below the 5th percentile. In conclusion, it is recommended that both clinicians and researchers use this battery in the evaluation of Mexican people with AD to better understand the prognosis of the disease and its subsequent treatment.

Comprehensive short and long read sequencing analysis for the Gaucher and Parkinson's disease-associated GBA gene

GBA variants carriers are at increased risk of Parkinson’s disease (PD) and Lewy body dementia (LBD). The presence of pseudogene GBAP1 predisposes to structural variants, complicating genetic analysis. We present two methods to resolve recombinant alleles and other variants in GBA: Gauchian, a tool for short-read, whole-genome sequencing data analysis, and Oxford Nanopore sequencing after PCR enrichment. Both methods were concordant for 42 samples carrying a range of recombinants and GBAP1-related mutations, and Gauchian outperformed the GATK Best Practices pipeline. Applying Gauchian to sequencing of over 10,000 individuals shows that copy number variants (CNVs) spanning GBAP1 are relatively common in Africans. CNV frequencies in PD and LBD are similar to controls. Gains may coexist with other mutations in patients, and a modifying effect cannot be excluded. Gauchian detects more GBA variants in LBD than PD, especially severe ones. These findings highlight the importance of accurate GBA analysis in these patients.

Two methods fully resolve the GBA gene: Gauchian, a tool for short-read, whole-genome sequencing data analysis, and Oxford Nanopore sequencing after PCR enrichment. The approach improves our understanding of the relationship between GBA, Gaucher disease and Parkinson disease.

Genome-wide association of polygenic risk extremes for Alzheimer's disease in the UK Biobank

In just over a decade, advances in genome-wide association studies (GWAS) have offered an approach to stratify individuals based on genetic risk for disease. Using recent Alzheimer's disease (AD) GWAS results as the base data, we determined each individual's polygenic risk score (PRS) in the UK Biobank dataset. Using individuals within the extreme risk distribution, we performed a GWAS that is agnostic of AD phenotype and is instead based on known genetic risk for disease. To interpret the functions of the new risk factors, we conducted phenotype analyses, including a phenome-wide association study. We identified 246 loci surpassing the significance threshold of which 229 were not reported in the base AD GWAS. These include loci that showed suggestive levels of association in the base GWAS and loci not previously suspected to be associated with AD. Among these, there are loci, such as IL34 and KANSL1, that have since been shown to be associated with AD in recent studies. We also show highly significant genetic correlations with multiple health-related outcomes that provide insights into prodromal symptoms and comorbidities. This is the first study to utilize PRS as a phenotype-agnostic group classification in AD genetic studies. We identify potential new loci for AD and detail phenotypic analysis of these PRS extremes.

A comprehensive analysis of copy number variation in a Turkish dementia cohort

BACKGROUND

Copy number variants (CNVs) include deletions or multiplications spanning genomic regions. These regions vary in size and may span genes known to play a role in human diseases. As examples, duplications and triplications of SNCA have been shown to cause forms of Parkinson's disease, while duplications of APP cause early onset Alzheimer's disease (AD).

RESULTS

Here, we performed a systematic analysis of CNVs in a Turkish dementia cohort in order to further characterize the genetic causes of dementia in this population. One hundred twenty-four Turkish individuals, either at risk of dementia due to family history, diagnosed with mild cognitive impairment, AD, or frontotemporal dementia, were whole-genome genotyped and CNVs were detected. We integrated family analysis with a comprehensive assessment of potentially disease-associated CNVs in this Turkish dementia cohort. We also utilized both dementia and non-dementia individuals from the UK Biobank in order to further elucidate the potential role of the identified CNVs in neurodegenerative diseases. We report CNVs overlapping the previously implicated genes ZNF804A, SNORA70B, USP34, XPO1, and a locus on chromosome 9 which includes a cluster of olfactory receptors and ABCA1. Additionally, we also describe novel CNVs potentially associated with dementia, overlapping the genes AFG1L, SNX3, VWDE, and BC039545.

CONCLUSIONS

Genotyping data from understudied populations can be utilized to identify copy number variation which may contribute to dementia.