Abstract: A variational autoencoder, comprising an encoder neural network and a decoder neural network, is configured to process a plurality of non-sequence altering change marker inputs, and to encode them in a non-sequence altering change latent space, which comprises respective feature embeddings that compress respective non-sequence altering change marker inputs in the plurality of non-sequence altering change marker inputs into a jointly Gaussian distribution. A method for predictive diagnosis of rheumatoid arthritis (RA) in a patient is also disclosed. Selected marker genes associated with patients having rheumatoid arthritis are formed by methods including deep learning analysis (e.g., via the variational autoencoder). A patient's blood products are assayed to detect the marker genes associated with rheumatoid arthritis. Selected marker genes include RCNA3, HDAC4, and SIPA1. The method may be extended to detect diseases different than or in addition to rheumatoid arthritis.

Abstract: We propose a method of generating an epigenetic age prediction. The method includes providing a sample extraction test kit, and receiving a sample extracted by the sample extraction test kit. The method further includes extracting DNA from the sample and processing the DNA to receive processed DNA. The method further includes amplifying a plurality of loci in the processed DNA to receive amplified DNA and processing the amplified DNA to receive a plurality of methylation values for one or more CpG sites in the plurality of loci.

Abstract: We propose a method of generating an epigenetic age prediction. The method includes providing a sample extraction test kit, and receiving a sample extracted by the sample extraction test kit. The method further includes extracting DNA from the sample and processing the DNA to receive processed DNA. The method further includes amplifying a plurality of loci in the processed DNA to receive amplified DNA and processing the amplified DNA to receive a plurality of methylation values for one or more CpG sites in the plurality of loci.

Abstract: We propose an epigenetic age predictor and a method of training the same. The epigenetic age predictor is configured to receive a plurality of inputs corresponding to methylation values at CpG sites. The epigenetic age predictor predicts an epigenetic age of an individual based on the plurality of inputs.

Abstract: We propose an epigenetic age predictor and a method of training the same. The epigenetic age predictor is configured to receive a plurality of inputs corresponding to methylation values at CpG sites. The epigenetic age predictor is configured to receive a plurality of inputs corresponding to phenotypic values of an individual. The epigenetic age predictor predicts an epigenetic age of the individual based on the sequence of inputs.