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Review
.2014 Mar 27;157(1):241-53.
doi: 10.1016/j.cell.2014.02.012.

Individualized medicine from prewomb to tomb

Affiliations
Review

Individualized medicine from prewomb to tomb

Eric J Topol. Cell..

Abstract

That each of us is truly biologically unique, extending to even monozygotic, "identical" twins, is not fully appreciated. Now that it is possible to perform a comprehensive "omic" assessment of an individual, including one's DNA and RNA sequence and at least some characterization of one's proteome, metabolome, microbiome, autoantibodies, and epigenome, it has become abundantly clear that each of us has truly one-of-a-kind biological content. Well beyond the allure of the matchless fingerprint or snowflake concept, these singular, individual data and information set up a remarkable and unprecedented opportunity to improve medical treatment and develop preventive strategies to preserve health.

Copyright © 2014 Elsevier Inc. All rights reserved.

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Figures

Figure 1
Figure 1. Geographic information system (GIS) of a human being
The ability to digitize the medical essence of a human being is predicated on the integration of multi-scale data, akin to a Google map, which consists of superimposed layers of data such as street, traffic and satellite views. For a human being, these layers include demographics and the social graph, biosensors to capture the individual's physiome, imaging to depict the anatomy (often along with physiologic data), and the biology from the various omics (genome-DNA sequence, transcriptome, proteome, metabolome, microbiome, and epigenome). In addition to all these layers, there is one's important environmental exposure data, known as the “exposome.”
Figure 2
Figure 2. Plots of panoromic information
a) Circos plot from the Snyderome Circos plot summarizing the Snyder genome. From outer to inner rings: chromosome ideogram; genomic data (pale blue ring), structural variants >50 bp (deletions [blue tiles], duplications [red tiles]), indels (green triangles); transcriptomic data (yellow ring), expression ratio of viral infection to healthy states; proteomic data (light purple ring), ratio of protein levels during human rhinovirus (HRV) infection to healthy states; transcriptomic data (yellow ring), differential heteroallelic expression ratio of alternative allele to reference allele for missense and synonymous variants (purple dots) and candidate RNA missense and synonymous edits (red triangles, purple dots, orange triangles and green dots, respectively). FromFrom (Chen et al., 2012) with permission. (b) Adopted London Tube Model of Integrated Omics from Shendure and Aiken Integration of the many applications of next-generation DNA sequencing which include: sites of DNA methylation (Methyl-Seq), Protein-DNA interactions (CHIP-Seq), 3-dimensional genome structure (Hi-C), genetically targeted purification of polysomal mRNAs (TRAP), the B-cell and T-cell repertoires (Immuno-Seq), and functional consequences of genetic variation (Synthetic saturation mutagenesis) with a small set of core techniques, represented as open circles of “stations.” Like subway lines, individual sequencing experiments move from station to station, until they ultimately arrive at a common terminal: DNA sequencing. From (Shendure and Lieberman Aiden, 2012) with permission.
Figure 2
Figure 2. Plots of panoromic information
a) Circos plot from the Snyderome Circos plot summarizing the Snyder genome. From outer to inner rings: chromosome ideogram; genomic data (pale blue ring), structural variants >50 bp (deletions [blue tiles], duplications [red tiles]), indels (green triangles); transcriptomic data (yellow ring), expression ratio of viral infection to healthy states; proteomic data (light purple ring), ratio of protein levels during human rhinovirus (HRV) infection to healthy states; transcriptomic data (yellow ring), differential heteroallelic expression ratio of alternative allele to reference allele for missense and synonymous variants (purple dots) and candidate RNA missense and synonymous edits (red triangles, purple dots, orange triangles and green dots, respectively). FromFrom (Chen et al., 2012) with permission. (b) Adopted London Tube Model of Integrated Omics from Shendure and Aiken Integration of the many applications of next-generation DNA sequencing which include: sites of DNA methylation (Methyl-Seq), Protein-DNA interactions (CHIP-Seq), 3-dimensional genome structure (Hi-C), genetically targeted purification of polysomal mRNAs (TRAP), the B-cell and T-cell repertoires (Immuno-Seq), and functional consequences of genetic variation (Synthetic saturation mutagenesis) with a small set of core techniques, represented as open circles of “stations.” Like subway lines, individual sequencing experiments move from station to station, until they ultimately arrive at a common terminal: DNA sequencing. From (Shendure and Lieberman Aiden, 2012) with permission.
Figure 3
Figure 3. Hypothetical plot of Cost of Sequencing and Number of Individuals Sequenced over the next 6 years
As of early 2014,<100,000 individuals have had whole genome sequencing with leaving the information difficult to fully interpret (of limited informativeness or value). When millions of people undergo sequencing, with the full gamut of diverse phenotypes and ancestries, and the cost for sequencing continues to drop, a virtuous cycle of informativeness is established. With the new capability in 2014 to have whole genome sequencing at a cost of $1000 along with extremely high throughput, it is likely that millions of individuals will be sequenced in the next 3–4 years. The cost of sequencing will continue to drop throughout this time, as the increasing numbers of individuals undergo sequencing. Projections suggest that at least 20,000 individuals with each phenotype may be necessary to reliably identify rare, functional genomic variants. Accordingly, once millions of individuals across all main phenotypes and ancestries are sequenced, there is a new set point, or threshold, of informativeness.
Figure 4
Figure 4. Timeline of Sequencing Applications in Medicine from Pre-Womb to Tomb
The medical application of genomics is relevant to many points during an individual's lifespan. Prior to conception, a couple can have genomic screening for important recessive alleles. An expectant mother, at 8–12 weeks of pregnancy, can now have single tube of blood used to accurately assess chromosomal abnormalities of the fetus, determine gender, and even have whole genome sequencing of the fetus performed. At birth, sequencing the genome of the newborn can be used to rapidly diagnosis many critical conditions for which a time delay, which frequently can occur with the present heel stick screening methods, might lead to irrevocable damage. The molecular basis for serious, undiagnosed conditions can often be established by sequencing the individual with parents of siblings. Ultimately, omic information at a young age will be useful by providing susceptibility to various medical conditions that have actionable prevention strategies. Sequencing can be done to define a pathogen for more rapid and accurate approaches to infectious diseases. The driver mutations and key biologic underpinning pathways of an individual's cancer can frequently be pinpointed by omics. The root causes of common polygenic conditions such as diabetes or coronary heart disease may ultimately be defined at the individual level. Specific sequence variants of germline DNA or the gut microbiome have relevance for response to prescription medication (both efficacy and safety). Defining the genomics of healthspan, rather than the traditional focus on diseases, may prove to be especially worthwhile to understand protective alleles and modifier genes. For an individual with sudden death, a molecular autopsy via sequencing can be performed, along with family survivors, to determine the cause of death and potentially prevent untimely or avoidable deaths of members of the family and subsequent generations.
Figure 5
Figure 5. Legend From Whole Genome Sequencing to Identification of a Causative Variant
Following sequencing, alignment and annotation, the 3.5 million variants, all genetic variants in the family (unaffected and affected individuals) are analyzed to identify known disease variants. Then inheritance-based and population-based filters are applied. Phenotype-informed ranking and functional filters are used to then determine the root-cause variant. The timeline for this involves (1) sample preparation of 2 days; (2) sequencing of 2 days in fast output mode; and the (3) preliminary analysis in ~24 hours (6 hrs for variant calling, 1 hr annotation, 1 hr for each candidate variant) and (4) literature review to exclude and include genes hit by potential candidate variants, an additional ~5 days. The cost for analysis is predominantly personnel and compute time on the cloud, estimated to be ~$300.
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References

    1. ALEXANDROV LB, NIK-ZAINAL S, WEDGE DC, APARICIO SA, BEHJATI S, BIANKIN AV, BIGNELL GR, BOLLI N, BORG A, BORRESEN-DALE AL, BOYAULT S, BURKHARDT B, BUTLER AP, CALDAS C, DAVIES HR, DESMEDT C, EILS R, EYFJORD JE, FOEKENS JA, GREAVES M, HOSODA F, HUTTER B, ILICIC T, IMBEAUD S, IMIELINSKI M, JAGER N, JONES DT, JONES D, KNAPPSKOG S, KOOL M, LAKHANI SR, LOPEZ-OTIN C, MARTIN S, MUNSHI NC, NAKAMURA H, NORTHCOTT PA, PAJIC M, PAPAEMMANUIL E, PARADISO A, PEARSON JV, PUENTE XS, RAINE K, RAMAKRISHNA M, RICHARDSON AL, RICHTER J, ROSENSTIEL P, SCHLESNER M, SCHUMACHER TN, SPAN PN, TEAGUE JW, TOTOKI Y, TUTT AN, VALDES-MAS R, VAN BUUREN MM, VAN 'T VEER L, VINCENT-SALOMON A, WADDELL N, YATES LR, AUSTRALIAN PANCREATIC CANCER GENOME, I. CONSORTIUM IBC, CONSORTIUM IM-S, PEDBRAIN I, ZUCMAN-ROSSI J, FUTREAL PA, MCDERMOTT U, LICHTER P, MEYERSON M, GRIMMOND SM, SIEBERT R, CAMPO E, SHIBATA T, PFISTER SM, CAMPBELL PJ, STRATTON MR. Signatures of mutational processes in human cancer. Nature. 2013;500:415–21. - PMC - PubMed
    1. ALMELING R. The Unregulated Sperm Industry. Times; New York: 2013. [Accessed 12/01/2013]. Online. Available:http://ow.ly/rsnVh.
    1. ARUMUGAM M, RAES J, PELLETIER E, LE PASLIER D, YAMADA T, MENDE DR, FERNANDES GR, TAP J, BRULS T, BATTO JM, BERTALAN M, BORRUEL N, CASELLAS F, FERNANDEZ L, GAUTIER L, HANSEN T, HATTORI M, HAYASHI T, KLEEREBEZEM M, KUROKAWA K, LECLERC M, LEVENEZ F, MANICHANH C, NIELSEN HB, NIELSEN T, PONS N, POULAIN J, QIN J, SICHERITZ-PONTEN T, TIMS S, TORRENTS D, UGARTE E, ZOETENDAL EG, WANG J, GUARNER F, PEDERSEN O, DE VOS WM, BRUNAK S, DORE J, META HITC, ANTOLIN M, ARTIGUENAVE F, BLOTTIERE HM, ALMEIDA M, BRECHOT C, CARA C, CHERVAUX C, CULTRONE A, DELORME C, DENARIAZ G, DERVYN R, FOERSTNER KU, FRISS C, VAN DE GUCHTE M, GUEDON E, HAIMET F, HUBER W, VAN HYLCKAMA-VLIEG J, JAMET A, JUSTE C, KACI G, KNOL J, LAKHDARI O, LAYEC S, LE ROUX K, MAGUIN E, MERIEUX A, MELO MINARDI R, M'RINI C, MULLER J, OOZEER R, PARKHILL J, RENAULT P, RESCIGNO M, SANCHEZ N, SUNAGAWA S, TORREJON A, TURNER K, VANDEMEULEBROUCK G, VARELA E, WINOGRADSKY Y, ZELLER G, WEISSENBACH J, EHRLICH SD, BORK P. Enterotypes of the human gut microbiome. Nature. 2011;473:174–80. - PMC - PubMed
    1. BATTICH N, STOEGER T, PELKMANS L. Image-based transcriptomics in thousands of single human cells at single-molecule resolution. Nat Methods. 2013;10:1127–33. - PubMed
    1. BEDARD PL, HANSEN AR, RATAIN MJ, SIU LL. Tumour heterogeneity in the clinic. Nature. 2013;501:355–64. - PMC - PubMed

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