Karel Kalecký

Introduction: Disturbances in one-carbon metabolism and homocysteine (Hcy) regulation have been implicated in Alzheimer's disease (AD) and Parkinson's disease (PD), yet direct evidence from human brain tissue and the contribution of genetic variation remain limited. We investigated whether B-vitamin-related metabolic deficits and polymorphisms in one-carbon metabolism pathways contribute to cognitive impairment in AD and PD. Methods: We quantitated metabolites related to B vitamins and one-carbon metabolism in post-mortem frontal cortex (n=136) and putamen (n=68) from clinically and neuropathologically characterized healthy controls, AD dementia (AD-D), PD with dementia (PD-D), PD with mild cognitive impairment (PD-MCI), and cognitively normal PD (PD-CN). Genotyping targeted variants related to one-carbon metabolism and B vitamins. Multivariable regression models controlled for demographic, clinical, metabolic, and tissue-handling covariates. Results: AD-D and PD-D shared a convergent cortical signature of reduced biotin, pyridoxal-5'-phosphate, thiamine monophosphate, pantothenic acid, and betaine. Elevated Hcy and reduced tetrahydrofolate were specific to AD-D and to PD-D during acute levodopa exposure. PD-MCI exhibited deficits in putamen resembling cortical dementia-associated changes. Self-reported B-vitamin supplementation attenuated several abnormalities, including complete normalization of levodopa-associated Hcy and folate disturbances in PD-D. Across subjects, multiple B vitamins showed strong associations with Hcy and betaine, indicating coordinated impairment of all three Hcy-metabolizing pathways. Genotyping analysis identified polymorphisms in MTRR, TYMS, MTR, NFE2L2, BHMT, and MTHFR that were differentially distributed across cognitive subgroups or associated with AD-related pathology scores. Composite genetic and metabolic burden scores were elevated in cognitively impaired groups but not in cognitively normal groups. Conclusion: Dementia in AD and PD is characterized by convergent B-vitamin deficiencies and genetic susceptibilities that disrupt Hcy metabolism. These findings provide a mechanistic explanation for levodopa-related Hcy accumulation in vulnerable PD subjects and identify B-vitamin supplementation as a potentially modifiable factor relevant to cognitive decline.

Structured INTRODUCTION: Metabolic dysregulation is a hallmark of Alzheimer’s disease (AD), but its temporal relationship to disease phenotypes remains unclear. METHODS: We analyzed 506 serum metabolites in 4,063 longitudinal samples from 1,430 Alzheimer’s Disease Neuroimaging Initiative participants using cross-sectional single-timepoint analysis, joint multi-timepoint analysis, and time-interaction analysis. RESULTS: Across 15 AD-related phenotypes, 311 metabolites were significantly associated with disease. Joint multi-timepoint analysis identified 281 metabolites, 243 in cross-sectional analyses, and 19 in time-interaction analysis. Associated metabolites implicated fatty acid and energy metabolism, neurotransmitter pathways, and oxidative stress regulation. Overall, 128 metabolites showed persistent associations over time, consistent with chronic systemic metabolic disruption. Only a small subset, including betaine, choline, and few amino acids, showed steeper declines with worsening AD endophenotypes. DISCUSSION: These findings indicate that most metabolic alterations in AD remain stable once established, while fewer continue to change during progression, clarifying the timing of metabolic dysregulation across the AD trajectory.

SUMMARY: The etiology of Alzheimer’s Disease (AD) remains largely unclear but is likely driven by gene-environment interactions. Here, we present a multi-organ untargeted metabolomics dataset (2,271 samples) generated from five tissue types in two genetic AD mouse models under colonized or germ-free conditions, complemented by shotgun metagenomics sequencing data (666 samples). Systems-level analyses of 3xTg and 5xFAD mice reveal clusters of dysregulated molecular classes across tissues including carnitines, bile acids, B vitamins, and neurotransmitters. This signature, coupled with microbiome profiles, suggests increased oxidative stress via mitochondrial dysfunction. Molecular feature tracking via tissueMASST, a mass spectrometry search tool we developed to bridge animal model findings with human data, identifies microbially-modulated phenylacetyl-carnitine as positively associated with aging and cognitive impairment across human AD studies. With hundreds of yet-to-be-characterized metabolites, this public resource and its associated tools will aid future research in the pathophysiology of AD.

We performed liquid chromatography tandem mass spectrometry analysis with the targeted metabolomic kit Biocrates MxP Quant 500, in human brain cortex (Brodmann area 9) and putamen, to reveal metabolic changes characteristic of Parkinson’s disease (PD) and PD-related cognitive decline. This case-control study involved 101 subjects (33 PD without dementia, 32 PD with dementia (cortex only), 36 controls). We found changes associated with PD, cognitive status, levodopa levels, and disease progression. The affected pathways include neurotransmitters, bile acids, homocysteine metabolism, amino acids, TCA cycle, polyamines, β-alanine metabolism, fatty acids, acylcarnitines, ceramides, phosphatidylcholines, and several microbiome-derived metabolites. Previously reported levodopa-related homocysteine accumulation in cortex still best explains the dementia status in PD, which can be modified by dietary supplementation. Further investigation is needed to reveal the exact mechanisms behind this pathological change.

Disruptions in one-carbon metabolism and elevated homocysteine have been previously implicated in the development of dementia associated with Alzheimer’s disease (AD) and Parkinson’s disease (PD). Moreover, a PD diagnosis itself carries substantial risk for the development of dementia. This is the first study that explores alterations in one-carbon metabolism in AD and PD directly in the human brain frontal cortex, the primary center of cognition. Applying targeted liquid chromatography–tandem mass spectrometry (LC-MS/MS), we analyzed post-mortem samples obtained from 136 subjects (35 AD, 65 PD, 36 controls). We found changes in one-carbon metabolites that indicate inefficient activation of cystathionine β-synthase (CBS) in AD and PD subjects with dementia, the latter seemingly accompanied by a restricted re-methylation flow. Levodopa–carbidopa is known to reduce available vitamin B6, which would explain the hindered CBS activity. We present evidence of temporary non-protein-bound homocysteine accumulation upon levodopa intake in the brain of PD subjects with dementia but not in non-demented PD subjects. Importantly, this homocysteine elevation is not related to levodopa dosage, disease progression, or histopathological markers but exclusively to the dementia status. We hypothesize that this levodopa-induced effect is a direct cause of dementia in PD in susceptible subjects with reduced re-methylation capacity. Furthermore, we show that betaine best correlates with cognitive score even among PD subjects alone and discuss nutritional recommendations to improve one-carbon metabolism function.

Cross-species analysis of large-scale protein–protein interaction (PPI) networks has played a significant role in understanding the principles deriving evolution of cellular organizations and functions. Recently, network alignment algorithms have been proposed to predict conserved interactions and functions of proteins. These approaches are based on the notion that orthologous proteins across species are sequentially similar and that topology of PPIs between orthologs is often conserved. However, high accuracy and scalability of network alignment are still a challenge. We propose a novel pairwise global network alignment algorithm, called PrimAlign, which is modeled as a Markov chain and iteratively transited until convergence. The proposed algorithm also incorporates the principles of PageRank. This approach is evaluated on tasks with human, yeast and fruit fly PPI networks. The experimental results demonstrate that PrimAlign outperforms several prevalent methods with statistically significant differences in multiple evaluation measures. PrimAlign, which is multi-platform, achieves superior performance in runtime with its linear asymptotic time complexity. Further evaluation is done with synthetic networks and results suggest that popular topological measures do not reflect real precision of alignments. The source code is available at http://web.ecs.baylor.edu/faculty/cho/PrimAlign. Supplementary data are available at Bioinformatics online.